Este dataset retorna dados tais como Categorias dos produtos vendidos, Valor médio de produto vendido e Categoria com maior quantidade de anúncios.
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=online_ads.filter(totalads=10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"online_ads.filter(totalads=10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Para usar esse campo de limite, basta utilizar o parâmetro .limit(x), mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=online_ads.limit(10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"online_ads.limit(10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados referentes aos colegas de classe da faculdade relacionados à pessoa buscada, tais como total de entidades relacionadas, média de idade e nível de escolaridade das entidades relacionadas.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nEste dataset retorna dados referentes aos Households relacionados à pessoa buscada, tais como total de entidades relacionadas, média de idade e nível de escolaridade das entidades relacionadas.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nEste dataset retorna dados referentes aos parentes relacionados à pessoa buscada, tais como total de entidades relacionadas, média de idade e nível de escolaridade das entidades relacionadas.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nEste dataset retorna dados referentes aos parentes de 1º grau relacionados à pessoa buscada, tais como total de entidades relacionadas, média de idade e nível de escolaridade das entidades relacionadas.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nEste dataset retorna dados referentes aos parceiros comerciais relacionados à pessoa buscada, tais como total de entidades relacionadas, média de idade e nível de escolaridade das entidades relacionadas.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nEste dataset retorna dados referentes aos colegas de trabalho relacionados à pessoa buscada, tais como total de entidades relacionadas, média de idade e nível de escolaridade das entidades relacionadas.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nEste dataset retorna dados referentes à pessoas que participaram de processos judiciais do mesmo lado da causa, com relação à pessoa buscada.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nEste dataset retorna dados referentes aos vizinhos relacionados à pessoa buscada, tais como total de entidades relacionadas, média de idade e nível de escolaridade das entidades relacionadas.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nEste dataset retorna dados referentes aos vizinhos que moram no mesmo prédio relacionados à pessoa buscada, tais como total de entidades relacionadas, média de idade e nível de escolaridade das entidades relacionadas.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nEste dataset retorna dados tais como Nome, CPF e Nome da mãe.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nEste dataset retorna dados tais como Profissão formal, Trabalho autônomo informal e Professores universitários.
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=occupation_data.filter(companyname=xxxxxxxx)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"occupation_data.filter(companyname=xxxxxxxx)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Conselhos de classe e entidades classistas, UF de registro e Status de atividade.
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=class_organization.filter(status=ATIVO)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"class_organization.filter(status=ATIVO)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Indicador e detalhes de Servidor Público, Órgão público e Remuneração.
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=profession_data.filter(companyname=xxxxxxxx)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"profession_data.filter(companyname=xxxxxxxx)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Indicador de estudante universitário, Detalhes CNPQ e Detalhes da residência médica.
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=university_student_data.filter(level=undergraduate)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"university_student_data.filter(level=undergraduate)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Para utilizar o campo de limite basta utilizar o parâmetro .limit(x), mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=university_student_data.limit(10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"university_student_data.limit(10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Dados de captura, Dados de volume de acesso e Dados de estrutura.
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=domains.filter(framework=xxxxxxxx)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"domains.filter(framework=xxxxxxxx)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Para utilizar o campo de limite basta utilizar o parâmetro .limit(x), mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=domains.limit(10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"domains.limit(10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Endreço(s) de e-mail, Tipo do e-mail e Indicadores de Utilização.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=emails.filter(type=work)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"emails.filter(type=work)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Para utilizar o campo de limite basta utilizar o parâmetro .limit(x), mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=emails.limit(10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"emails.limit(10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Dataset que tem como retorno os dados de endereços de email das entidades relacionadas à pessoa buscada.
\nParâmetro Opcional
\n","urlObject":{"protocol":"https","path":["peoplev2"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"65a23662-8e8a-43f2-84c4-82ef24dcde8a","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/peoplev2?Datasets=related_people_emails&q=doc{xxxxxxxxxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["peoplev2"],"query":[{"key":"Datasets","value":"related_people_emails"},{"key":"q","value":"doc{xxxxxxxxxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"RelatedPeopleEmails\": [\n {\n \"EmailAddress\": \"teste@hotmail.com\",\n \"Domain\": \"hotmail.com\",\n \"UserName\": \"teste\",\n \"Type\": \"RELATED - xxxxxxxxxxx - BROTHER - personal\",\n \"EmailTotalPassages\": 1,\n \"EmailBadPassages\": 0,\n \"EmailCrawlingPassages\": -1,\n \"EmailValidationPassages\": -1,\n \"EmailQueryPassages\": -1,\n \"EmailMonthAveragePassages\": 1,\n \"EmailNumberOfEntities\": 2,\n \"Priority\": 1,\n \"IsMain\": true,\n \"IsRecent\": false,\n \"IsActive\": true,\n \"ValidationStatus\": \"VALID\",\n \"LastValidationDate\": \"2017-05-15T00:00:00Z\",\n \"FirstPassageDate\": \"2011-11-26T00:00:00Z\",\n \"LastPassageDate\": \"2011-11-26T00:00:00Z\",\n \"CreationDate\": \"2011-11-26T00:00:00Z\",\n \"LastUpdateDate\": \"2015-10-08T00:00:00Z\"\n }\n ]\n }\n ],\n \"QueryId\": \"a3e02f04-d49d-4cc7-83a0-98d42943bfcf\",\n \"ElapsedMilliseconds\": 793,\n \"Status\": {\n \"related_people_emails\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"6c1001dc-5096-42cc-a022-814d7a7cbd42","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"related_people_emails\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2"},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"RelatedPeopleEmails\": [\n {\n \"EmailAddress\": \"teste@hotmail.com\",\n \"Domain\": \"hotmail.com\",\n \"UserName\": \"teste\",\n \"Type\": \"RELATED - xxxxxxxxxxx - BROTHER - personal\",\n \"EmailTotalPassages\": 1,\n \"EmailBadPassages\": 0,\n \"EmailCrawlingPassages\": -1,\n \"EmailValidationPassages\": -1,\n \"EmailQueryPassages\": -1,\n \"EmailMonthAveragePassages\": 1,\n \"EmailNumberOfEntities\": 2,\n \"Priority\": 1,\n \"IsMain\": true,\n \"IsRecent\": false,\n \"IsActive\": true,\n \"ValidationStatus\": \"VALID\",\n \"LastValidationDate\": \"2017-05-15T00:00:00Z\",\n \"FirstPassageDate\": \"2011-11-26T00:00:00Z\",\n \"LastPassageDate\": \"2011-11-26T00:00:00Z\",\n \"CreationDate\": \"2011-11-26T00:00:00Z\",\n \"LastUpdateDate\": \"2015-10-08T00:00:00Z\"\n }\n ]\n }\n ],\n \"QueryId\": \"a3e02f04-d49d-4cc7-83a0-98d42943bfcf\",\n \"ElapsedMilliseconds\": 793,\n \"Status\": {\n \"related_people_emails\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"1dadda6f-dcc3-4cc4-b780-4cc7de4fc1c5"},{"name":"Endereços","id":"873d2910-9e7e-419e-a310-2a168e48cd71","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"addresses\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2","description":"Este dataset retorna dados tais como Endereço detalhado, Tipo do endereço e Indicador endereço principal.
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=addresses.filter(type=work)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"addresses.filter(type=work)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Para utilizar o campo de limite basta utilizar o parâmetro .limit(x), mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=addresses.limit(10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"addresses.limit(10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Dataset que tem como retorno os dados de endereços das entidades relacionadas à pessoa buscada.
\nParâmetro Opcional
\n","urlObject":{"protocol":"https","path":["peoplev2"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"4718b292-00ba-4246-9930-ec7b769b220f","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"related_people_addresses\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2"},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"RelatedPeopleAddresses\": [\n {\n \"Typology\": \"RUA\",\n \"Title\": \"\",\n \"AddressMain\": \"ALEXANDRE RAMOS\",\n \"Number\": \"147\",\n \"Complement\": \"\",\n \"Neighborhood\": \"TANQUE\",\n \"ZipCode\": \"22735140\",\n \"City\": \"RIO DE JANEIRO\",\n \"State\": \"RJ\",\n \"Country\": \"Brazil\",\n \"Type\": \"RELATED - xxxxxxxxxxx - BROTHER - WORK\",\n \"HouseholdCode\": \"55-AB-FD-78-71-78-82-D1-F1-DE-03-2A-8C-04-7B-26\",\n \"BuildingCode\": \"55-AB-FD-78-71-78-82-D1-F1-DE-03-2A-8C-04-7B-26\",\n \"HouseholdTotalPassages\": 2,\n \"HouseholdBadPassages\": 0,\n \"HouseholdCrawlingPassages\": 0,\n \"HouseholdValidationPassages\": 0,\n \"HouseholdQueryPassages\": -1,\n \"HouseholdMonthAveragePassages\": 0,\n \"BuildingTotalPassages\": 2,\n \"BuildingBadPassages\": 0,\n \"BuildingCrawlingPassages\": 0,\n \"BuildingValidationPassages\": 0,\n \"BuildingQueryPassages\": -1,\n \"BuildingMonthAveragePassages\": 0,\n \"BuildingNumberOfHouseholds\": -1,\n \"Priority\": 1,\n \"IsMain\": true,\n \"IsRecent\": false,\n \"IsActive\": true,\n \"IsRatified\": true,\n \"FirstPassageDate\": \"2015-08-01T00:00:00Z\",\n \"LastPassageDate\": \"2015-08-01T00:00:00Z\",\n \"CreationDate\": \"2015-08-01T00:00:00Z\",\n \"LastUpdateDate\": \"2015-08-01T00:00:00Z\",\n \"HasOptIn\": false,\n \"AdditionalOutputData\": {\n \"IbgeCode\": \"3304557\"\n },\n \"Latitude\": -22.9220599,\n \"Longitude\": -43.35954\n }\n ]\n }\n ],\n \"QueryId\": \"a3e02f04-d49d-4cc7-83a0-98d42943bfcf\",\n \"ElapsedMilliseconds\": 793,\n \"Status\": {\n \"related_people_addresses\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"ae53d323-4e15-469a-9693-fd807d1736ea","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/peoplev2?Datasets=related_people_addresses&q=doc{xxxxxxxxxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["peoplev2"],"query":[{"key":"Datasets","value":"related_people_addresses"},{"key":"q","value":"doc{xxxxxxxxxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"RelatedPeopleAddresses\": [\n {\n \"Typology\": \"RUA\",\n \"Title\": \"\",\n \"AddressMain\": \"ALEXANDRE RAMOS\",\n \"Number\": \"147\",\n \"Complement\": \"\",\n \"Neighborhood\": \"TANQUE\",\n \"ZipCode\": \"22735140\",\n \"City\": \"RIO DE JANEIRO\",\n \"State\": \"RJ\",\n \"Country\": \"Brazil\",\n \"Type\": \"RELATED - xxxxxxxxxxx - BROTHER - WORK\",\n \"HouseholdCode\": \"55-AB-FD-78-71-78-82-D1-F1-DE-03-2A-8C-04-7B-26\",\n \"BuildingCode\": \"55-AB-FD-78-71-78-82-D1-F1-DE-03-2A-8C-04-7B-26\",\n \"HouseholdTotalPassages\": 2,\n \"HouseholdBadPassages\": 0,\n \"HouseholdCrawlingPassages\": 0,\n \"HouseholdValidationPassages\": 0,\n \"HouseholdQueryPassages\": -1,\n \"HouseholdMonthAveragePassages\": 0,\n \"BuildingTotalPassages\": 2,\n \"BuildingBadPassages\": 0,\n \"BuildingCrawlingPassages\": 0,\n \"BuildingValidationPassages\": 0,\n \"BuildingQueryPassages\": -1,\n \"BuildingMonthAveragePassages\": 0,\n \"BuildingNumberOfHouseholds\": -1,\n \"Priority\": 1,\n \"IsMain\": true,\n \"IsRecent\": false,\n \"IsActive\": true,\n \"IsRatified\": true,\n \"FirstPassageDate\": \"2015-08-01T00:00:00Z\",\n \"LastPassageDate\": \"2015-08-01T00:00:00Z\",\n \"CreationDate\": \"2015-08-01T00:00:00Z\",\n \"LastUpdateDate\": \"2015-08-01T00:00:00Z\",\n \"HasOptIn\": false,\n \"AdditionalOutputData\": {\n \"IbgeCode\": \"3304557\"\n },\n \"Latitude\": -22.9220599,\n \"Longitude\": -43.35954\n }\n ]\n }\n ],\n \"QueryId\": \"a3e02f04-d49d-4cc7-83a0-98d42943bfcf\",\n \"ElapsedMilliseconds\": 793,\n \"Status\": {\n \"related_people_addresses\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"639d5780-6e08-4721-9561-f1f72d85ecd7"},{"name":"Addresses - Related People","id":"c9120bde-97d8-49dd-b8dc-37431b6ec9b3","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","name":"Content-Type","type":"text","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"related_people_addresses\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2","description":"Dataset which returns addresses from related people.
\nOptional parameter
\n","urlObject":{"protocol":"https","path":["peoplev2"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"2032a03a-fc18-4108-b617-b7868646d0c3","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/peoplev2?Datasets=related_people_addresses&q=doc{xxxxxxxxxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["peoplev2"],"query":[{"key":"Datasets","value":"related_people_addresses"},{"key":"q","value":"doc{xxxxxxxxxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"RelatedPeopleAddresses\": [\n {\n \"Typology\": \"RUA\",\n \"Title\": \"\",\n \"AddressMain\": \"ALEXANDRE RAMOS\",\n \"Number\": \"147\",\n \"Complement\": \"\",\n \"Neighborhood\": \"TANQUE\",\n \"ZipCode\": \"22735140\",\n \"City\": \"RIO DE JANEIRO\",\n \"State\": \"RJ\",\n \"Country\": \"Brazil\",\n \"Type\": \"RELATED - xxxxxxxxxxx - BROTHER - WORK\",\n \"HouseholdCode\": \"55-AB-FD-78-71-78-82-D1-F1-DE-03-2A-8C-04-7B-26\",\n \"BuildingCode\": \"55-AB-FD-78-71-78-82-D1-F1-DE-03-2A-8C-04-7B-26\",\n \"HouseholdTotalPassages\": 2,\n \"HouseholdBadPassages\": 0,\n \"HouseholdCrawlingPassages\": 0,\n \"HouseholdValidationPassages\": 0,\n \"HouseholdQueryPassages\": -1,\n \"HouseholdMonthAveragePassages\": 0,\n \"BuildingTotalPassages\": 2,\n \"BuildingBadPassages\": 0,\n \"BuildingCrawlingPassages\": 0,\n \"BuildingValidationPassages\": 0,\n \"BuildingQueryPassages\": -1,\n \"BuildingMonthAveragePassages\": 0,\n \"BuildingNumberOfHouseholds\": -1,\n \"Priority\": 1,\n \"IsMain\": true,\n \"IsRecent\": false,\n \"IsActive\": true,\n \"IsRatified\": true,\n \"FirstPassageDate\": \"2015-08-01T00:00:00Z\",\n \"LastPassageDate\": \"2015-08-01T00:00:00Z\",\n \"CreationDate\": \"2015-08-01T00:00:00Z\",\n \"LastUpdateDate\": \"2015-08-01T00:00:00Z\",\n \"HasOptIn\": false,\n \"AdditionalOutputData\": {\n \"IbgeCode\": \"3304557\"\n },\n \"Latitude\": -22.9220599,\n \"Longitude\": -43.35954\n }\n ]\n }\n ],\n \"QueryId\": \"a3e02f04-d49d-4cc7-83a0-98d42943bfcf\",\n \"ElapsedMilliseconds\": 793,\n \"Status\": {\n \"related_people_addresses\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"75e37acc-72ee-4f57-8cfc-4d33ded8cfc5","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"related_people_addresses\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2"},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"RelatedPeopleAddresses\": [\n {\n \"Typology\": \"RUA\",\n \"Title\": \"\",\n \"AddressMain\": \"ALEXANDRE RAMOS\",\n \"Number\": \"147\",\n \"Complement\": \"\",\n \"Neighborhood\": \"TANQUE\",\n \"ZipCode\": \"22735140\",\n \"City\": \"RIO DE JANEIRO\",\n \"State\": \"RJ\",\n \"Country\": \"Brazil\",\n \"Type\": \"RELATED - xxxxxxxxxxx - BROTHER - WORK\",\n \"HouseholdCode\": \"55-AB-FD-78-71-78-82-D1-F1-DE-03-2A-8C-04-7B-26\",\n \"BuildingCode\": \"55-AB-FD-78-71-78-82-D1-F1-DE-03-2A-8C-04-7B-26\",\n \"HouseholdTotalPassages\": 2,\n \"HouseholdBadPassages\": 0,\n \"HouseholdCrawlingPassages\": 0,\n \"HouseholdValidationPassages\": 0,\n \"HouseholdQueryPassages\": -1,\n \"HouseholdMonthAveragePassages\": 0,\n \"BuildingTotalPassages\": 2,\n \"BuildingBadPassages\": 0,\n \"BuildingCrawlingPassages\": 0,\n \"BuildingValidationPassages\": 0,\n \"BuildingQueryPassages\": -1,\n \"BuildingMonthAveragePassages\": 0,\n \"BuildingNumberOfHouseholds\": -1,\n \"Priority\": 1,\n \"IsMain\": true,\n \"IsRecent\": false,\n \"IsActive\": true,\n \"IsRatified\": true,\n \"FirstPassageDate\": \"2015-08-01T00:00:00Z\",\n \"LastPassageDate\": \"2015-08-01T00:00:00Z\",\n \"CreationDate\": \"2015-08-01T00:00:00Z\",\n \"LastUpdateDate\": \"2015-08-01T00:00:00Z\",\n \"HasOptIn\": false,\n \"AdditionalOutputData\": {\n \"IbgeCode\": \"3304557\"\n },\n \"Latitude\": -22.9220599,\n \"Longitude\": -43.35954\n }\n ]\n }\n ],\n \"QueryId\": \"a3e02f04-d49d-4cc7-83a0-98d42943bfcf\",\n \"ElapsedMilliseconds\": 793,\n \"Status\": {\n \"related_people_addresses\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"c9120bde-97d8-49dd-b8dc-37431b6ec9b3"},{"name":"Exposição e Perfil na Mídia ","id":"c811ae79-f04d-4f9a-ac4d-17cc285b8975","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"media_profile_and_exposure\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2","description":"Este dataset retorna dados tais como Indicador de nível de exposição na mídia, Indicador de nível de celebridade e Indicador de impopularidade. A consulta Exposição e Perfil na Mídia aceita os seguintes parâmetros para busca:
\nParâmetro Obrigatório
\nParâmetro Opcional
\nPaginação: a paginação do dataset pode ser feita através do parâmetro next utilizando o ID retornado por cada requisição conforme exemplo abaixo:
\nhttps://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=media_profile_and_exposure.next(ID da próxima página)&
\nq=&
\nAccessToken=
Abaixo exemplificamos uma chamada Get e Post:
\nGet:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=media_profile_and_exposure&
\nq=name{seu_nome}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"media_profile_and_exposure\",
\n \"q\": \"name{seu_nome} \",
\n \"AccessToken\": \"\"
\n}
Exemplo de chamadas utilizando o filtro:
\nGet:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=media_profile_and_exposure**.filter(sourcename=xxxxxxxx)**&
\nq=name{seu_nome}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"media_profile_and_exposure**.filter(sourcename=xxxxxxxx)**\",
\n \"q\": \"name{seu_nome} \",
\n \"AccessToken\": \"\"
\n}
Para utilizar o campo de limite basta utilizar o parâmetro .limit(x), mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=media_profile_and_exposure.limit(10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"media_profile_and_exposure.limit(10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Findability geral, Findability por e-mail e Indicador de estabilidade de emprego.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nSeguem abaixo os nomes de modelos e suas possveis descriçoes:
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=flags_and_features.filter(modelinputkey=document)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"flags_and_features.filter(modelinputkey=document)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Renda estimada, Dados de restituição do Imposto de Renda e Agência e banco de recebimento da restituição.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\n***** SM: Salário Mínimo *****
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=financial_data.filter(taxreturns_year=2015)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"financial_data.filter(taxreturns_year=2015)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Dados sócio-demográficos IBGE e outras fontes.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\n***** SM: Salário Mínimo *****
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=demographic_data.filter(dataorigin=mte)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"demographic_data.filter(dataorigin=mte)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Indicador de PPE nacional, Presença em listas de terroristas e Presença em listas de lavagem de dinheiro.
\nParâmetro Obrigatório
\nParâmetro Opcional
\nValores de retorno
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=kyc.filter(sanctions_source=interpol)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"kyc.filter(sanctions_source=interpol)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Nível de utilização de cartão de crédito, Participação em programas de milhagem e Interesse por categoria.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nAtenção
\nNessa consulta é cobrado o custo por atributo individual dentro do Dataset. Caso deseje selecionar apenas alguns atributos, é possível usar o select conforme exemplo abaixo:
\nGet:
\nDatasets=interests_and_behaviors{SportAndLeisure,Housewares,CreditCardScore}
Post:
\n\"Datasets\"=\"interests_and_behaviors{SportAndLeisure,Housewares,CreditCardScore}\"
Abaixo seguem as categorias de interesse retornadas nesse dataset
\n","urlObject":{"protocol":"https","path":["peoplev2"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"4297a329-d39a-4b6a-a3d5-6517722b9467","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"interests_and_behaviors\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2"},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"InterestsAndBehaviors\": {\n \"Behaviors\": {\n\t\t \"ProductReseller\": \"False\",\n\t\t \"CreditCardScore\": \"A\",\n\t\t \"MilesProgram\": \"False\",\n\t\t \"OnlineInvestor\": \"True\"\n\t\t },\n\t\t \"CategoriesOfInterest\": {\n\t\t \"Automotive\": 0,\n\t\t \"Baby\": 0,\n\t\t \"BeautyAndHealth\": 0,\n\t\t \"BeverageAndFood\": 0,\n\t\t \"Bodybuilding\": 0,\n\t\t \"Books\": 0,\n\t\t \"Computing\": 0,\n\t\t \"Delivery\": 0,\n\t\t \"Eletronics\": 0,\n\t\t \"Entertainment\": 0,\n\t\t \"FashionAndAcessories\": 0,\n\t\t \"Games\": 0,\n\t\t \"HomeAndDecoration\": 0,\n\t\t \"Housewares\": 0,\n\t\t \"MobileTelco\": 0,\n\t\t \"MusicalInstruments\": 0,\n\t\t \"Service\": 0,\n\t\t \"SportAndLeisure\": 0,\n\t\t \"Streaming\": 0,\n\t\t \"Toys\": 0,\n\t\t \"TravelAndTourism\": 0\n\t\t }\n }\n }\n ],\n \"QueryId\": \"ce928a4d-62b5-4817-8503-42abad08ae80\",\n \"ElapsedMilliseconds\": 145,\n \"Status\": {\n \"niches\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"78bf2f33-0616-4787-b709-21d0b1bfa278","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/peoplev2?Datasets=interests_and_behaviors&q=doc{xxxxxxxxxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["peoplev2"],"query":[{"key":"Datasets","value":"interests_and_behaviors"},{"key":"q","value":"doc{xxxxxxxxxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"InterestsAndBehaviors\": {\n \"Behaviors\": {\n\t\t \"ProductReseller\": \"False\",\n\t\t \"CreditCardScore\": \"A\",\n\t\t \"MilesProgram\": \"False\",\n\t\t \"OnlineInvestor\": \"True\"\n\t\t },\n\t\t \"CategoriesOfInterest\": {\n\t\t \"Automotive\": 0,\n\t\t \"Baby\": 0,\n\t\t \"BeautyAndHealth\": 0,\n\t\t \"BeverageAndFood\": 0,\n\t\t \"Bodybuilding\": 0,\n\t\t \"Books\": 0,\n\t\t \"Computing\": 0,\n\t\t \"Delivery\": 0,\n\t\t \"Eletronics\": 0,\n\t\t \"Entertainment\": 0,\n\t\t \"FashionAndAcessories\": 0,\n\t\t \"Games\": 0,\n\t\t \"HomeAndDecoration\": 0,\n\t\t \"Housewares\": 0,\n\t\t \"MobileTelco\": 0,\n\t\t \"MusicalInstruments\": 0,\n\t\t \"Service\": 0,\n\t\t \"SportAndLeisure\": 0,\n\t\t \"Streaming\": 0,\n\t\t \"Toys\": 0,\n\t\t \"TravelAndTourism\": 0\n\t\t }\n }\n }\n ],\n \"QueryId\": \"ce928a4d-62b5-4817-8503-42abad08ae80\",\n \"ElapsedMilliseconds\": 145,\n \"Status\": {\n \"niches\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"862ea88c-fe04-491f-8c9d-04953cc3f942"},{"name":"Passagens pela Web ","id":"b8b18879-f576-4b83-bbed-acb225748196","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"passages\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2","description":"Este dataset retorna dados tais como Frequência de passagens pela web, Recência da passagem pela web e Frequência de passagens suspeitas pela web.
\nEste dataset retorna dados tais como Indicador de comprador online, Nível de utilização da internet e Frequência de operações na internet.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nEste dataset retorna dados tais como Indicador de presença em cobrança, Recência da consulta de cobrança e Quantidade de origens de cobrança.
\nEste dataset retorna dados tais como Número dos Processos, Quantidade total de processos que uma pessoa possui e Quantidade total de processos que uma pessoa possui como autor.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nSeguem abaixo alguns campos que podem ser utilizados como filtro na busca:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=processes.filter(state=rj)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"processes.filter(state=rj)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Para sar esse campo de limite, basta utilizar o parâmetro .limit(x), mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=processes.limit(10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"processes.limit(10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Indicador de participação no Bolsa Família.
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=social_assistance.filter(programstate=RJ)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"social_assistance.filter(programstate=RJ)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Sócios e Participação em empresas.
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=business_relationships.filter(relationshiptype=employment,relatedentitytaxidtype=CPF)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"business_relationships.filter(relationshiptype=employment,,relatedentitytaxidtype=CPF)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Para usar o campo de limite, basta utilizar o parâmetro .limit(x), mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=business_relationships.limit(10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"business_relationships.limit(10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Parentes, Vizinhos e Colegas de trabalho.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=related_people.filter(relationshiptype=mother)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"related_people.filter(relationshiptype=mother)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Para usar o campo de limite, basta utilizar o parâmetro .limit(x), mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=related_people.limit(10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"related_people.limit(10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Número(s) de telefone, Indicador PROCON e Indicador de telefone principal.
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=phones.filter(ismain=true)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"phones.filter(ismain=true)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Para usar o campo de limite, basta utilizar o parâmetro .limit(x), mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=phones.limit(10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"phones.limit(10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Dataset que tem como retorno os dados de endereços das entidades relacionadas à pessoa buscada.
\nParâmetro Opcional
\n","urlObject":{"protocol":"https","path":["peoplev2"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"3de4cdad-b087-4025-b88e-d9f056abb4b3","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/peoplev2?Datasets=related_people_phones&q=doc{xxxxxxxxxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["peoplev2"],"query":[{"key":"Datasets","value":"related_people_phones"},{"key":"q","value":"doc{xxxxxxxxxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"RelatedPeoplePhones\": [\n {\n \"Number\": \"32164715\",\n \"AreaCode\": \"91\",\n \"CountryCode\": \"55\",\n \"Complement\": \"\",\n \"Type\": \"WORK\",\n \"PhoneTotalPassages\": 84,\n \"PhoneBadPassages\": 0,\n \"PhoneCrawlingPassages\": 84,\n \"PhoneValidationPassages\": 0,\n \"PhoneQueryPassages\": -1,\n \"PhoneMonthAveragePassages\": 2,\n \"Priority\": 1,\n \"IsMain\": true,\n \"IsRecent\": false,\n \"IsActive\": false,\n \"IsInDoNotCallList\": false,\n \"CurrentCarrier\": \"\",\n \"PlanType\": \"\",\n \"FirstPassageDate\": \"2017-08-05T00:00:00Z\",\n \"LastPassageDate\": \"2017-08-17T00:00:00Z\",\n \"CreationDate\": \"2014-06-01T00:00:00Z\",\n \"LastUpdateDate\": \"2017-08-17T00:00:00Z\",\n \"PortabilityHistory\": [\n {\n \"OriginalCareer\": \"\",\n \"NewCareer\": \"\",\n \"PortabilityDate\": \"2017-11-18T00:00:00Z\"\n }\n ],\n \"HasOptIn\": false\n }\n ]\n }\n ],\n \"QueryId\": \"a3e02f04-d49d-4cc7-83a0-98d42943bfcf\",\n \"ElapsedMilliseconds\": 793,\n \"Status\": {\n \"related_people_addresses\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"ca31454a-1777-458a-8eee-e066b87a927d","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"related_people_phones\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2"},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"RelatedPeoplePhones\": [\n {\n \"Number\": \"32164715\",\n \"AreaCode\": \"91\",\n \"CountryCode\": \"55\",\n \"Complement\": \"\",\n \"Type\": \"WORK\",\n \"PhoneTotalPassages\": 84,\n \"PhoneBadPassages\": 0,\n \"PhoneCrawlingPassages\": 84,\n \"PhoneValidationPassages\": 0,\n \"PhoneQueryPassages\": -1,\n \"PhoneMonthAveragePassages\": 2,\n \"Priority\": 1,\n \"IsMain\": true,\n \"IsRecent\": false,\n \"IsActive\": false,\n \"IsInDoNotCallList\": false,\n \"CurrentCarrier\": \"\",\n \"PlanType\": \"\",\n \"FirstPassageDate\": \"2017-08-05T00:00:00Z\",\n \"LastPassageDate\": \"2017-08-17T00:00:00Z\",\n \"CreationDate\": \"2014-06-01T00:00:00Z\",\n \"LastUpdateDate\": \"2017-08-17T00:00:00Z\",\n \"PortabilityHistory\": [\n {\n \"OriginalCareer\": \"\",\n \"NewCareer\": \"\",\n \"PortabilityDate\": \"2017-11-18T00:00:00Z\"\n }\n ],\n \"HasOptIn\": false\n }\n ]\n }\n ],\n \"QueryId\": \"a3e02f04-d49d-4cc7-83a0-98d42943bfcf\",\n \"ElapsedMilliseconds\": 793,\n \"Status\": {\n \"related_people_addresses\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"0a6e1f28-c802-489f-8139-ca9f18bf6302"},{"name":"Veículos","id":"cfd1f718-1fd7-462a-a7e0-395bbe21efde","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"vehicles\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2","description":"Dataset retorna dados referentes aos veiculos relacionados ao documento buscado.
\nSegue abaixo a tabela com a descrição dos campos
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=vehicles.filter(modelyear=2017)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"vehicles.filter(modelyear=2017)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Para usar o campo de limite, basta utilizar o parâmetro .limit(x), mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=vehicles.limit(10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"vehicles.limit(10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
A API de pessoas engloba todas as consultas relacionadas a pessoas. O catálogo de dados pode ser visualizado através da seguinte URL:
\nhttps://www.bigdatacorp.info/datasets-de-pessoas
Para a realização de consultas são necessários o preenchimento de alguns parâmetros, que estão mostrados na tabela abaixo:
O parâmetro q engloba todas as chaves de busca. Ao realizar uma consulta por documento (CPF) recomendarmos a busca por CPF por ser mais assertiva e sempre ligada a apenas uma pessoa, nem sempre nossos clientes tem o CPF para consultar. Por isso, além do CPF, o BigBoost permite que o usuário realize consultas com uma série de parâmetros adicionais. Alguns desses parâmetros são arrays, que podem receber mais de elemento, separados por vírgula. Dos parâmetros abaixo, pelo um deles precisa ser preenchido para realizar as buscas para atribuição de CPF:
Além desses, temos também os parâmetros opcionais, que servem de filtro para ter um resultado mais assertivo:\n
Os parâmetros de entrada devem ser concatenados por vírgula. O exemplo abaixo mostra uma consulta por nome e data de nascimento. As chaves podem ser combinadas de acordo com a necessidade do usuário.
**Get: **
\nq=name{seu nome},birthdate{10/02/1995},dateformat{dd/MM/yyyy}
**Post: **
\n\"q\"=\"name{seu nome},birthdate{10/02/1995},dateformat{dd/MM/yyyy}\"
Para objetos em formato de array como phone, também pode-se utilizar colchetes.
\n**Get: **
\nq=name{seu nome},phone[21967654532,21976556234]
**Post: **
\n\"q\"=\"name{seu nome},phone[21967654532,21976556234]\"
As chaves podem ser combinadas de acordo com a necessidade do usuário. Por padrão, a API retornará apenas uma pessoa mesmo que encontre mais de uma associada as informações de entrada. Para aumentar esse limite basta utilizar o parâmetro Limit, mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=seus_datasets&
\nq=name{seu nome},birthdate{10/02/1995},dateformat{dd/MM/yyyy}&
\nAccessToken=&Limit=5
Post:
Body:
\n{
\n \"Datasets\": \"seus_datasets\",
\n \"q\": \"name{seu nome},birthdate{10/02/1995},dateformat{dd/MM/yyyy} \",
\n \"AccessToken\": \"\",
\n \"Limit\"=\"5\"
\n}
CUIDADO: o custo da consulta é por cada dataset consultado, ou seja, se encontrarmos 2 pessoas e enriquecermos com um dataset, a cobrança será o valor desse dataset vezes as 2 pessoas enriquecidas.
O parâmetro Datasets contempla todo o conjunto de dados que deverá ser utilizado para a consulta. Abaixo listamos os datasets disponibilizados na API de Pessoas:
O nome dos datasets devem ser separados por vírgulas dentro do parâmetro Datasets. Caso o usuário queira\nconsultar dados básicos, telefones e e-mails por exemplo, o parâmetro Datasets deve ser preenchido da seguinte\nmaneira:
Como a lista de datasets selecionada pode ser muito grande, é possível associar esse conjunto de datasets a uma\nview através da nossa API de Views. Uma view é um alias para um conjunto de datasets. Caso você opte por criar\numa view, direcione sua leitura para a sessão API de Views.
\n","event":[{"listen":"prerequest","script":{"id":"29531317-3428-4450-8565-27c06e7edbc1","type":"text/javascript","exec":[""]}},{"listen":"test","script":{"id":"ddc6d43f-b5d0-4691-bdd5-00585358501d","type":"text/javascript","exec":[""]}}],"_postman_id":"34b53093-79a2-44d1-9c79-ccd116de5df7"},{"name":"API de Empresas","item":[{"name":"Anúncios Online","id":"8f026c66-e8a9-48ac-a31c-fd550e84659a","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"online_ads\",\r\n\t\"q\": \"doc{xxxxxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/companies","description":"Este dataset retorna dados tais como Categorias dos produtos vendidos, Valor médio de produto vendido e Média de anúncios nos últimos \"n\" dias.
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=online_ads.filter(totalads=10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"online_ads.filter(totalads=10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Para usar esse campo de limite, basta utilizar o parâmetro .limit(x), mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=online_ads.limit(10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"online_ads.limit(10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Razão social, CNPJ e Status na Receita Federal.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nEste dataset retorna dados tais como Dados de classificação, Dados de tecnologias básicas e Dados de integração com mídias sociais.
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=domains.filter(framework=xxxxxxxx)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"domains.filter(framework=xxxxxxxx)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Para utilizar o campo de limite basta utilizar o parâmetro .limit(x), mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=domains.limit(10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"domains.limit(10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Endereço(s) de e-mail, Indicadores de Frequência e Indicadores de Utilização.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_cmapo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=emails.filter(type=work)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"emails.filter(type=work)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Para usar esse campo de limite, basta utilizar o parâmetro .limit(x), mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=emails.limit(10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"emails.limit(10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Endereço detalhado, Tipo do endereço e Indicadores de Utilização.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=addresses.filter(ismain=true)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"addresses.filter(ismain=true)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Para utilizar esse campo de limite, basta utilizar o parâmetro .limit(x), mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=addresses.limit(10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"addresses.limit(10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Indicador de nível de exposição na mídia, Indicador de nível de celebridade e Indicador de impopularidade.
\nA consulta Exposição e Perfil na Mídia aceita os seguintes parâmetros para busca:
\nParâmetro Obrigatório
\nParâmetro Opcional
\nPaginação: a paginação do dataset pode ser feita através do parâmetro next utilizando o ID retornado por cada requisição conforme exemplo abaixo:
\nhttps://bigboost.bigdatacorp.com.br/companies?
\nDatasets=media_profile_and_exposure.next(ID da próxima página)&
\nq=&
\nAccessToken=
Abaixo exemplificamos uma chamada Get e Post:
\nGet:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=media_profile_and_exposure&
\nq=name{nome_empresa}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"media_profile_and_exposure\",
\n \"q\": \"name{nome_empresa} \",
\n \"AccessToken\": \"\"
\n}
Exemplo de chamadas utilizando o filtro:
\nGet:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=media_profile_and_exposure**.filter(sourcename=xxxxxxxx)**&
\nq=name{seu_nome}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"media_profile_and_exposure**.filter(sourcename=xxxxxxxx)**\",
\n \"q\": \"name{seu_nome} \",
\n \"AccessToken\": \"\"
\n}
Abaixo segue a tabela que contempla alguns campos e seus retornos:
\nPor padrão, esse dataset irá retornar 4 dados. Para aumentar esse limite basta utilizar o parâmetro .limit(x), mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=economic_group_data.limit(10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"economic_group_data.limit(10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Atividade operacional, Número de funcionários e Faturamento estimado.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nEste dataset retorna dados tais como Indicador de PPE nacional, Presença em listas de terroristas e Presença em listas de lavagem de dinheiro.
\nParâmetro Obrigatório
\nParâmetro Opcional
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=kyc.filter(sanctions_source=interpol)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"kyc.filter(sanctions_source=interpol)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Número dos Processos, Quantidade total de processos que uma empresa possui e Quantidade total de processos que uma empresa possui como autora.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nSeguem abaixo alguns campos que podem ser utilizados como filtro na busca:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=processes.filter(state=sp)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"processes.filter(state=sp)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Para utilizar esse campo de limite, basta utilizar o parâmetro .limit(x), mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=processes.limit(10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"processes.limit(10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Sócios (pessoas ou empresas), Funcionários e Participação em empresas.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=relationships.filter(relatedentitytaxidtype=CPF)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"relationships.filter(relatedentitytaxidtype=CPF)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Para utilizar esse campo de limite, basta utilizar o parâmetro .limit(x), mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=relationships.limit(10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"relationships.limit(10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Este dataset retorna dados tais como Número(s) de telefone, Tipo do telefone e Indicadores de Frequência.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\nNesse dataset é possível filtrar alguns campos, que estão mostrados na tabela abaixo juntamente com os parâmetros que são aceitos como filtro:
\nAbaixo está um exemplo de como utilizar o parâmetro .filter(nome_do_campo=xxxx), mostrado na URL exemplo nos métodos GET e POST:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=phones.filter(ismain=true)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"phones.filter(ismain=true)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Para usar o campo de limite, basta utilizar o parâmetro .limit(x), mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=phones.limit(10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"phones.limit(10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
A API de empresas engloba todas as consultas relacionadas a empresas. O catálogo de dados pode ser visualizado\natravés da seguinte URL:
\nhttps://www.bigdatacorp.info/datasets-de-empresas
Para a realização de consultas são necessários o preenchimento de alguns parâmetros, que estão mostrados na tabela abaixo:
O parâmetro q engloba todas as chaves de busca. Ao realizar uma consulta por documento (CNPJ) recomendarmos a busca por CNPJ por ser mais assertiva e sempre ligada a apenas uma empresa, nem sempre nossos clientes tem o CNPJ para consultar. Por isso, além do CNPJ, o BigBoost permite que o usuário realize consultas com uma série de parâmetros adicionais. Alguns desses parâmetros são arrays, que podem receber mais de elemento, separados por vírgula. Dos parâmetros abaixo, pelo um deles precisa ser preenchido para realizar as buscas para atribuição de CNPJ:
Além desses, temos também os parâmetros opcionais, que servem de filtro para ter um resultado mais assertivo:\n
Os parâmetros de entrada devem ser concatenados por vírgula. Para objetos em formato de array como phone, também pode-se utilizar colchetes. Abaixo mostramos uma combinação desses parâmetros com uma consulta por nome, telefone e e-mail:
Get:
\nq=name{nome_empresa},phone[xxxxxxxx,xxxxxxxx],email[seu_email@email.com]
Post:
\n\"q\"=\"name{nome_empresa},phone[xxxxxxxx,xxxxxxxx],email[seu_email@email.com]\"
As chaves podem ser combinadas de acordo com a necessidade do usuário. Por padrão, a API retornará apenas uma empresa mesmo que encontre mais de uma associada as informações de entrada. Para aumentar esse limite basta utilizar o parâmetro Limit, mostrado na URL exemplo abaixo:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=seus_datasets&
\nq=name{nome_empresa},email{seu_email@email.com}&
\nAccessToken=&Limit=5
Post:
Body:
\n{
\n \"Datasets\": \"seus_datasets\",
\n \"q\": \"name{nome_empresa},email{seu_email@email.com} \",
\n \"AccessToken\": \"\",
\n \"Limit\"=\"5\"
\n}
CUIDADO: o custo da consulta é por cada dataset consultado, ou seja, se encontrarmos 2 empresas e\nenriquecermos com um dataset, a cobrança será o valor desse dataset vezes as 2 empresas enriquecidas.
O parâmetro Datasets contempla todo o conjunto de dados que deverá ser utilizado para a consulta. Abaixo listamos\nos datasets disponibilizados na API de Empresas:
O nome dos datasets devem ser separados por vírgulas dentro do parâmetro Datasets. Caso o usuário queira\nconsultar dados básicos, telefones e e-mails por exemplo, o parâmetro Datasets deve ser preenchido da seguinte\nmaneira:
Como a lista de datasets selecionada pode ser muito grande, é possível associar esse conjunto de datasets a uma\nview através da nossa API de Views. Uma view é um alias para um conjunto de datasets. Caso você opte por criar\numa view, direcione sua leitura para a sessão API de Views.
\n","event":[{"listen":"prerequest","script":{"id":"8e14c67e-3e79-424d-91ef-fe5e313f07e8","type":"text/javascript","exec":[""]}},{"listen":"test","script":{"id":"df681d1c-4c75-4363-9c74-ee5c74a5c525","type":"text/javascript","exec":[""]}}],"_postman_id":"05a5e7a4-b62e-42f3-bfa1-8444a8b06405"},{"name":"API de Misc","item":[{"name":"Estatísticas do E-mail","id":"13a46f77-e786-451a-9360-757d350e85e9","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"statistics_email\",\r\n\t\"q\": \"email{seu_email@email.com.br}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/misc","description":"Dataset retorna estatísticas sobre o email buscado.
\nDataset retorna informações estatísticas sobre o telefone buscado.
\nAbaixo segue a tabela que contempla alguns campos e seus retornos:
\n","urlObject":{"protocol":"https","path":["misc"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"e24693a4-9723-4187-bb30-3286d680cd1c","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"fipe_vehicle\",\r\n\t\"q\": \"brand{xxxx},model{xxxxx},year{xxxx},code{xxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/misc"},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"FipeVehicles\": [\n {\n \"Category\": \"CARROS\",\n \"Brand\": \"AGRALE\",\n \"Model\": \"MARRUA AM 100 2.8 CS TDI DIESEL\",\n \"FipeCode\": \"0600032\",\n \"ModelYear\": \"2015\",\n \"FuelType\": \"DIESEL\",\n \"AvgPrice\": \"113.114,00\",\n \"ReferenceMonth\": \"FEVEREIRO\",\n \"ReferenceYear\": \"2019\",\n \"CreationDate\": \"2019-03-01T04:33:09Z\",\n \"LastUpdateDate\": \"2019-03-01T04:33:09Z\"\n }\n ]\n }\n ],\n \"QueryId\": \"c7406a1d-acc2-432d-8501-3518851e509c\",\n \"ElapsedMilliseconds\": 445,\n \"Status\": {\n \"fipe_vehicle\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"f51d4ceb-f647-414e-8842-96a5c386a43c","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","name":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/misc?Datasets=fipe_vehicle&q=brand{xxxx},model{xxxxx},year{xxxx},code{xxxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["misc"],"query":[{"key":"Datasets","value":"fipe_vehicle"},{"key":"q","value":"brand{xxxx},model{xxxxx},year{xxxx},code{xxxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"FipeVehicles\": [\n {\n \"Category\": \"CARROS\",\n \"Brand\": \"AGRALE\",\n \"Model\": \"MARRUA AM 100 2.8 CS TDI DIESEL\",\n \"FipeCode\": \"0600032\",\n \"ModelYear\": \"2015\",\n \"FuelType\": \"DIESEL\",\n \"AvgPrice\": \"113.114,00\",\n \"ReferenceMonth\": \"FEVEREIRO\",\n \"ReferenceYear\": \"2019\",\n \"CreationDate\": \"2019-03-01T04:33:09Z\",\n \"LastUpdateDate\": \"2019-03-01T04:33:09Z\"\n }\n ]\n }\n ],\n \"QueryId\": \"c7406a1d-acc2-432d-8501-3518851e509c\",\n \"ElapsedMilliseconds\": 445,\n \"Status\": {\n \"fipe_vehicle\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"2a4f9c83-ee0e-4d66-84f8-1e7621a1c038"},{"name":"Fipe - Marcas","id":"7de8f13c-9e6e-4250-82d0-ab0b10ec0969","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"fipe_brands\",\r\n\t\"q\": \"category{xxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/misc","description":"Possíveis valores de categoria: \"CARROS\", \"CAMINHOES\" e \"MOTOS\"
\n","urlObject":{"protocol":"https","path":["misc"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"e51c0d74-c9c3-473f-b023-47dd56bab98d","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"fipe_brands\",\r\n\t\"q\": \"category{xxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/misc"},"status":"OK","code":200,"_postman_previewlanguage":"Text","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"FipeBrands\": [\n {\n \"Brand\": \"ACURA\"\n },\n {\n \"Brand\": \"AGRALE\"\n },\n {\n \"Brand\": \"ALFA ROMEO\"\n },\n {\n \"Brand\": \"AM GEN\"\n },\n {\n \"Brand\": \"ASIA MOTORS\"\n },\n {\n \"Brand\": \"ASTON MARTIN\"\n },\n {\n \"Brand\": \"AUDI\"\n }\n ]\n }\n ],\n \"QueryId\": \"25e6cb50-10d7-4249-b94d-c52f4db65691\",\n \"ElapsedMilliseconds\": 3187,\n \"Status\": {\n \"fipe_brands\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"fe8fdc46-8486-40e1-b522-f02a097a256c","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","name":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/misc?Datasets=fipe_brands&q=category{xxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["misc"],"query":[{"key":"Datasets","value":"fipe_brands"},{"key":"q","value":"category{xxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"FipeBrands\": [\n {\n \"Brand\": \"ACURA\"\n },\n {\n \"Brand\": \"AGRALE\"\n },\n {\n \"Brand\": \"ALFA ROMEO\"\n },\n {\n \"Brand\": \"AM GEN\"\n },\n {\n \"Brand\": \"ASIA MOTORS\"\n },\n {\n \"Brand\": \"ASTON MARTIN\"\n },\n {\n \"Brand\": \"AUDI\"\n }\n ]\n }\n ],\n \"QueryId\": \"25e6cb50-10d7-4249-b94d-c52f4db65691\",\n \"ElapsedMilliseconds\": 3187,\n \"Status\": {\n \"fipe_brands\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"7de8f13c-9e6e-4250-82d0-ab0b10ec0969"},{"name":"Fipe - Modelo","id":"01dfeb2b-3763-48de-993e-7b51dbe10924","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"fipe_models\",\r\n\t\"q\": \"category{xxxxx},brand{xxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/misc","description":"","urlObject":{"protocol":"https","path":["misc"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"0cd78bf4-d3c2-41cd-876e-939caccf6814","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","name":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/misc?Datasets=fipe_models&q=category{xxxxx},brand{xxxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["misc"],"query":[{"key":"Datasets","value":"fipe_models"},{"key":"q","value":"category{xxxxx},brand{xxxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"FipeModels\": [\n {\n \"Model\": \"100 2.8 V6\"\n },\n {\n \"Model\": \"100 2.8 V6 AVANT\"\n },\n {\n \"Model\": \"100 S-4 2.2 AVANT TURBO\"\n },\n {\n \"Model\": \"80 2.0\"\n },\n {\n \"Model\": \"80 2.0 AVANT\"\n }\n ]\n }\n ],\n \"QueryId\": \"1575056e-5349-4e61-8fee-e810ddad256c\",\n \"ElapsedMilliseconds\": 85,\n \"Status\": {\n \"fipe_models\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"dab738c3-035a-42b8-b817-079fe0123575","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"fipe_models\",\r\n\t\"q\": \"category{xxxxx},brand{xxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/misc"},"status":"OK","code":200,"_postman_previewlanguage":"Text","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"FipeModels\": [\n {\n \"Model\": \"100 2.8 V6\"\n },\n {\n \"Model\": \"100 2.8 V6 AVANT\"\n },\n {\n \"Model\": \"100 S-4 2.2 AVANT TURBO\"\n },\n {\n \"Model\": \"80 2.0\"\n },\n {\n \"Model\": \"80 2.0 AVANT\"\n }\n ]\n }\n ],\n \"QueryId\": \"1575056e-5349-4e61-8fee-e810ddad256c\",\n \"ElapsedMilliseconds\": 85,\n \"Status\": {\n \"fipe_models\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"01dfeb2b-3763-48de-993e-7b51dbe10924"},{"name":"Fipe - Ano Modelo","id":"25c02f0d-e727-4e95-bb9f-2a1c595f3d43","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"fipe_model_years\",\r\n\t\"q\": \"category{xxxxx},brand{xxxxx},model{xxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/misc","description":"","urlObject":{"protocol":"https","path":["misc"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"358e594f-b024-42ed-8a21-3277bb47365a","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"fipe_model_years\",\r\n\t\"q\": \"category{xxxxx},brand{xxxxx},model{xxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/misc"},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"FipeModelYears\": [\n {\n \"ModelYear\": \"1995\"\n },\n {\n \"ModelYear\": \"1994\"\n },\n {\n \"ModelYear\": \"1993\"\n }\n ]\n }\n ],\n \"QueryId\": \"31641415-57ed-4fd3-b68b-929bc8816877\",\n \"ElapsedMilliseconds\": 432,\n \"Status\": {\n \"fipe_model_years\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"3a143582-e302-4c74-9473-4890b0773110","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","name":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/misc?Datasets=fipe_model_years&q=category{xxxxx},brand{xxxxx},model{xxxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["misc"],"query":[{"key":"Datasets","value":"fipe_model_years"},{"key":"q","value":"category{xxxxx},brand{xxxxx},model{xxxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"FipeModelYears\": [\n {\n \"ModelYear\": \"1995\"\n },\n {\n \"ModelYear\": \"1994\"\n },\n {\n \"ModelYear\": \"1993\"\n }\n ]\n }\n ],\n \"QueryId\": \"31641415-57ed-4fd3-b68b-929bc8816877\",\n \"ElapsedMilliseconds\": 432,\n \"Status\": {\n \"fipe_model_years\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"25c02f0d-e727-4e95-bb9f-2a1c595f3d43"}],"id":"bbe14921-05f8-4fac-915e-4f822c477698","description":"Os datasets misc são conjuntos de dados que não estão estritamente amarrados com pessoas ou empresas, e geralmente associam outras entidades. Esses dados podem servir como fontes alternativas de geração de atributos derivados para processos de modelagem, ou podem ser utilizados em seu contexto natural para a construção de modelos de inteligência artificial.
\n","event":[{"listen":"prerequest","script":{"id":"f7de09b9-1bb4-40c0-9ed3-b711145a5306","type":"text/javascript","exec":[""]}},{"listen":"test","script":{"id":"23dff383-3739-402d-beb6-3ca27771dbc5","type":"text/javascript","exec":[""]}}],"_postman_id":"bbe14921-05f8-4fac-915e-4f822c477698"},{"name":"API de On Demand","item":[{"name":"API de Pessoas","item":[{"name":"Boa Vista (com Score)","id":"d91d7539-c9bc-4b06-948c-4d8d90fe2ab8","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"ondemand_credit_boavista_score\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2","description":"Retorna dados consultados direto da COAF (Conselho de Controle de Atividades Financeiras)
\nRetorna informações da Procuradoria-Geral da Fazenda Nacional.
\nA consulta Certidão de Nada Consta aceita os seguintes parâmetros para busca:
\nParâmetro Obrigatório
\nParâmetros Opcionais
\nPara os parâmetros opcionais são aceitos os seguintes argumentos:
\ncourt: TRF1 / TRF2 / TRF3 / TRF4 / TRF5.
\nop: CIVIL / CRIMINAL.
\nEsse dataset realiza consultas em tempo real, retornando dados da Receita Federal referentes ao CPF buscado.
\nAo passar a data de nascimento, deve-se também passar o formato em que a data de nascimento está sendo enviada na requisição. Por exemplo:
\nGet:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=ondemand_rf_status&
\nq=doc{xxxxxxxxxxx},birthdate{10-07-1998},dateformat{dd-MM-yyyy}\n&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"ondemand_rf_status\",
\n \"q\": \"doc{xxxxxxxxxxx},birthdate{10-07-1998},dateformat{dd-MM-yyyy}\",
\n \"AccessToken\": \"\",
\n}
A consulta Rais aceita o seguintes parâmetros para busca:
\nParâmetro Obrigatório
\nParâmetro Opcional
\n","urlObject":{"protocol":"https","path":["peoplev2"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"76b041ef-518b-469d-af8d-95a884044976","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"ondemand_cert_rais\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2"},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"OnlineQuery\": [\n {\n \"Origin\": \"Rais\",\n \"InputParameters\": \"doc{xxxxxxxxxxx}\",\n \"AdditionalOutputData\": {\n \"Name\": \"ANA KELEN DE CARVALHO\",\n \"Nit\": \"13098383274\",\n \"IdNumber.0\": \"\",\n \"OfficialName.0\": \"ESSENCE TERC MAO OBRA E SERVICOS LTDA\",\n \"Cnpj/Caepf/Cei/Cno.0\": \"06.290.395/0001-90\",\n \"DeliveryStatus.0\": \"ENTREGUE\",\n \"DtDelivery.0\": \"2018-03-22\",\n \"DtAdimission.0\": \"2016-09-01\"\n },\n \"QueryDate\": \"2019-03-27T20:33:08.8578526Z\"\n }\n ]\n }\n ],\n \"QueryId\": \"30a39d94-5739-43ac-aa60-6da44841c3c7\",\n \"ElapsedMilliseconds\": 1130,\n \"Status\": {\n \"ondemand_rais\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"c554d200-1cd6-4a78-b3c7-6d81e914a8a4","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/peoplev2?Datasets=ondemand_cert_rais&q=doc{xxxxxxxxxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["peoplev2"],"query":[{"key":"Datasets","value":"ondemand_cert_rais"},{"key":"q","value":"doc{xxxxxxxxxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"OnlineQuery\": [\n {\n \"Origin\": \"Rais\",\n \"InputParameters\": \"doc{xxxxxxxxxxx}\",\n \"AdditionalOutputData\": {\n \"Name\": \"ANA KELEN DE CARVALHO\",\n \"Nit\": \"13098383274\",\n \"IdNumber.0\": \"\",\n \"OfficialName.0\": \"ESSENCE TERC MAO OBRA E SERVICOS LTDA\",\n \"Cnpj/Caepf/Cei/Cno.0\": \"06.290.395/0001-90\",\n \"DeliveryStatus.0\": \"ENTREGUE\",\n \"DtDelivery.0\": \"2018-03-22\",\n \"DtAdimission.0\": \"2016-09-01\"\n },\n \"QueryDate\": \"2019-03-27T20:33:08.8578526Z\"\n }\n ]\n }\n ],\n \"QueryId\": \"30a39d94-5739-43ac-aa60-6da44841c3c7\",\n \"ElapsedMilliseconds\": 1130,\n \"Status\": {\n \"ondemand_rais\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"7796ccaf-48ba-495b-b9ec-4944f25c688b"},{"name":"SPC Brasil (com Score)","id":"783ab496-e6bf-4cb6-982a-289fb0e66f31","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"ondemand_credit_spc_score_12_months\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2","description":"A consulta de crédito do SPC com score possibilita 2 modelos de consulta: score em relação aos 3 últimos meses e em relação aos 12 últimos meses:
\n","urlObject":{"protocol":"https","path":["peoplev2"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"bfe87e3e-2f39-479b-afd7-7fe5d718dc03","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"ondemand_credit_spc_score_12_months\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2"},"status":"OK","code":200,"_postman_previewlanguage":"Text","header":[],"cookie":[],"responseTime":null,"body":"{\r\n \"Result\": [\r\n {\r\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\r\n \"CreditData\": [\r\n {\r\n \"Origin\": \"SPC\",\r\n \"QueryDate\": \"2018-08-13T00:00:00\",\r\n \"BasicData\": {\r\n \"TaxIdNumber\": \"xxxxxxxxxxx\",\r\n \"TaxIdCountry\": \"Brazil\",\r\n \"AlternativeIdNumbers\": {\r\n \"VoterRegistration\": \"\"\r\n },\r\n \"Name\": \"\",\r\n \"Gender\": \"\",\r\n 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A.\",\n \"BusinessName\": \"Embratel\",\n \"LastUpdateDate\": \"27/03/2019\",\n \"LastUpdateTime\": \"16:39\"\n },\n \"QueryDate\": \"2019-03-27T19:39:31.0625311Z\"\n }\n ]\n }\n ],\n \"QueryId\": \"84bea04b-dcd6-4d17-9c23-ee2ecdbb7bbf\",\n \"ElapsedMilliseconds\": 5020,\n \"Status\": {\n \"ondemand_phone_portability\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"e0be745a-19c6-4497-bcec-9d9bcccf781e","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","name":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/validations?Datasets=ondemand_phone_portability&q=phone{xxxxxxxxxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["validations"],"query":[{"key":"Datasets","value":"ondemand_phone_portability"},{"key":"q","value":"phone{xxxxxxxxxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"OnlineCertificates\": [\n {\n \"Origin\": \"ABRT\",\n \"InputParameters\": \"phone{2132513142}\",\n \"NormalizedInputs\": \"phone{2132513142}\",\n \"ValidationType\": \"Phone Operator\",\n \"MainValidationStatus\": \"VALID\",\n \"AdditionalValidationDetails\": {\n \"OfficialName\": \"EMPRESA BRASILEIRA DE TELECOMUNICACOES S. 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\"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/validations","description":"","urlObject":{"protocol":"https","path":["validations"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"3631a9cc-4f7b-41cc-b969-a77b6e9a521a","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","name":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"ondemand_email\",\r\n\t\"q\": \"email{seu_email@mail.com}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/validations"},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"OnlineCertificates\": [\n {\n \"Origin\": \"BDC E-mail Validation\",\n \"InputParameters\": \"email{marcus.rocha@gmail.com}\",\n \"NormalizedInputs\": \"email{marcus.rocha@gmail.com}\",\n \"ValidationType\": \"E-mail Validation\",\n \"MainValidationStatus\": \"VALID\",\n \"AdditionalValidationDetails\": {\n \"Account\": \"MARCUS.ROCHA\",\n \"Domain\": \"GMAIL.COM\",\n \"Disposable\": \"FALSE\",\n \"RoleAddress\": \"FALSE\"\n },\n \"QueryDate\": \"2019-03-27T19:40:12.5344061Z\"\n }\n ]\n }\n ],\n \"QueryId\": \"5324fde0-5410-423d-9d3c-22e1f83ef6e4\",\n \"ElapsedMilliseconds\": 471,\n \"Status\": {\n \"ondemand_email\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"ff8800b7-3a3e-4383-9655-013b1bf3af0b","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","name":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/validations?Datasets=ondemand_email&q=email{seu_email@mail.com}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["validations"],"query":[{"key":"Datasets","value":"ondemand_email"},{"key":"q","value":"email{seu_email@mail.com}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"OnlineCertificates\": [\n {\n \"Origin\": \"BDC E-mail Validation\",\n \"InputParameters\": \"email{marcus.rocha@gmail.com}\",\n \"NormalizedInputs\": \"email{marcus.rocha@gmail.com}\",\n \"ValidationType\": \"E-mail Validation\",\n \"MainValidationStatus\": \"VALID\",\n \"AdditionalValidationDetails\": {\n \"Account\": \"MARCUS.ROCHA\",\n \"Domain\": \"GMAIL.COM\",\n \"Disposable\": \"FALSE\",\n \"RoleAddress\": \"FALSE\"\n },\n \"QueryDate\": \"2019-03-27T19:40:12.5344061Z\"\n }\n ]\n }\n ],\n \"QueryId\": \"5324fde0-5410-423d-9d3c-22e1f83ef6e4\",\n \"ElapsedMilliseconds\": 471,\n \"Status\": {\n \"ondemand_email\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"03259e28-4bba-498d-927d-1231972c9e58"},{"name":"Validação do Telefone e Operadora na ABRT","id":"aa67cded-c3c2-48d8-bd6f-56019e0378f7","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"ondemand_phone_operator\",\r\n\t\"q\": \"phone{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/validations","description":"","urlObject":{"protocol":"https","path":["validations"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"9e6fe6bf-780a-4820-b49e-9d979ef1670b","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/validations?Datasets=ondemand_phone_operator&q=phone{xxxxxxxxxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["validations"],"query":[{"key":"Datasets","value":"ondemand_phone_operator"},{"key":"q","value":"phone{xxxxxxxxxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"OnlineCertificates\": [\n {\n \"Origin\": \"ABRT\",\n \"InputParameters\": \"phone{21992178909}\",\n \"NormalizedInputs\": \"phone{21992178909}\",\n \"ValidationType\": \"Portability History\",\n \"MainValidationStatus\": \"VALID\",\n \"AdditionalValidationDetails\": {\n \"OfficialName.0\": \"CLARO S.A.\",\n \"BusinessName.0\": \"Claro\",\n \"CurrentOperator.0\": \"True\",\n \"OfficialName.1\": \"TNL PCS S.A.\",\n \"BusinessName.1\": \"Oi Móvel\",\n \"PortabilityDate.1\": \"23/04/2009\",\n \"PortabilityTime.1\": \"08:02\",\n \"CurrentOperator.1\": \"False\",\n \"OfficialName.2\": \"VIVO S.A.\",\n \"BusinessName.2\": \"Vivo\",\n \"PortabilityDate.2\": \"27/06/2012\",\n \"PortabilityTime.2\": \"20:05\",\n \"CurrentOperator.2\": \"False\"\n },\n \"QueryDate\": \"2019-03-27T20:26:00.4328427Z\"\n }\n ]\n }\n ],\n \"QueryId\": \"acf22f0d-f0c9-4d62-9b98-f6f37a9a1235\",\n \"ElapsedMilliseconds\": 7594,\n \"Status\": {\n \"ondemand_phone_operator\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"d1f2abe1-7f29-4d22-9146-9807bdbb6cf6","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"ondemand_phone_operator\",\r\n\t\"q\": \"phone{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/validations"},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"OnlineCertificates\": [\n {\n \"Origin\": \"ABRT\",\n \"InputParameters\": \"phone{21992178909}\",\n \"NormalizedInputs\": \"phone{21992178909}\",\n \"ValidationType\": \"Portability History\",\n \"MainValidationStatus\": \"VALID\",\n \"AdditionalValidationDetails\": {\n \"OfficialName.0\": \"CLARO S.A.\",\n \"BusinessName.0\": \"Claro\",\n \"CurrentOperator.0\": \"True\",\n \"OfficialName.1\": \"TNL PCS S.A.\",\n \"BusinessName.1\": \"Oi Móvel\",\n \"PortabilityDate.1\": \"23/04/2009\",\n \"PortabilityTime.1\": \"08:02\",\n \"CurrentOperator.1\": \"False\",\n \"OfficialName.2\": \"VIVO S.A.\",\n \"BusinessName.2\": \"Vivo\",\n \"PortabilityDate.2\": \"27/06/2012\",\n \"PortabilityTime.2\": \"20:05\",\n \"CurrentOperator.2\": \"False\"\n },\n \"QueryDate\": \"2019-03-27T20:26:00.4328427Z\"\n }\n ]\n }\n ],\n \"QueryId\": \"acf22f0d-f0c9-4d62-9b98-f6f37a9a1235\",\n \"ElapsedMilliseconds\": 7594,\n \"Status\": {\n \"ondemand_phone_operator\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"aa67cded-c3c2-48d8-bd6f-56019e0378f7"}],"id":"9469a7d2-4b9e-47a7-9f64-7bcd76856a50","_postman_id":"9469a7d2-4b9e-47a7-9f64-7bcd76856a50","description":""}],"id":"aa82591f-74d2-42fc-8a9b-fd1e3568cfc4","description":"Os serviços on-demand são consultas executadas em tempo real, para as quais não faz sentido, ou é tecnicamente inviável, a manutenção de bases off-line e de histórico de dados consultados. Todos os serviços listados aqui estão disponíveis para chamada via API de forma separada dos outros dados.
\nA chamada de detalhes permite que o usuário visualize todas as views que estão associadas com aquele código de acesso (AccessToken). O nó de resultado contém uma lista com todas as views associadas bem como a descrição de cada uma.
\n","urlObject":{"protocol":"https","path":["views","Details"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"5dbcf32a-8b42-4f99-aa9b-499783fef8d7","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"AccessToken\": \"\"\r\n}\r\n\r\n"},"url":"https://bigboost.bigdatacorp.com.br/views/Details"},"status":"OK","code":200,"_postman_previewlanguage":"Text","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": {\n \"view_name_1\": {\n \"CreationDate\": \"2018-09-03T21:19:52.7162586Z\",\n \"LastUpdateDate\": \"2018-09-04T18:39:15.1957757Z\",\n \"Api\": \"People\",\n \"Datasets\": \"basic_data,emails\"\n },\n \"view_name_2\": {\n \"CreationDate\": \"2018-09-04T19:01:22.2353159Z\",\n \"LastUpdateDate\": \"2018-09-04T19:01:22.2353159Z\",\n \"Api\": \"Companies\",\n \"Datasets\": \"basic_data,phones,addresses\"\n }\n },\n \"QueryId\": \"253d6ab1-d620-4518-b9b8-9e516477bc0f\",\n \"ElapsedMilliseconds\": 20,\n \"Status\": {\n \"api\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"c0c69ce0-ade5-4d0c-8c49-273ac3549d3b","name":"GET","originalRequest":{"method":"GET","header":[],"url":{"raw":"https://bigboost.bigdatacorp.com.br/views/Details?AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["views","Details"],"query":[{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": {\n \"view_name_1\": {\n \"CreationDate\": \"2018-09-03T21:19:52.7162586Z\",\n \"LastUpdateDate\": \"2018-09-04T18:39:15.1957757Z\",\n \"Api\": \"People\",\n \"Datasets\": \"basic_data,emails\"\n },\n \"view_name_2\": {\n \"CreationDate\": \"2018-09-04T19:01:22.2353159Z\",\n \"LastUpdateDate\": \"2018-09-04T19:01:22.2353159Z\",\n \"Api\": \"Companies\",\n \"Datasets\": \"basic_data,phones,addresses\"\n }\n },\n \"QueryId\": \"253d6ab1-d620-4518-b9b8-9e516477bc0f\",\n \"ElapsedMilliseconds\": 20,\n \"Status\": {\n \"api\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"11ca8dd6-b95f-4e57-9ac3-3c136306d515"},{"name":"Atualizar","id":"3264eb61-13b0-4763-88eb-9f10aa888d98","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Api\": \"nome_da_api\",\r\n\t\"Datasets\": \"seu_dataset1,seu_dataset2,seu_dataset3\",\r\n\t\"View\": \"sua_view\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/views/Update","description":"A API de Views permite que você salve um conjunto de datasets para ser utilizado nas demais APIs de consulta. A vantagem de criar uma view é que uma vez criada, o usuário não precisará mais informar o conjunto de datasets na URL de enriquecimento visto que já estarão associados a view.
\nPara a realização de consultas usando Views são necessários o preenchimento de alguns parâmetros que estão mostrados na tabela abaixo:
\nUma view funciona como um alias para um conjunto de dados, onde todas as chamadas são feitas através de requisições HTTP/HTTPS via Get ou Post. Abaixo exemplificamos o formato da URL que deve ser utilizada para uma chamada Get e Post para uma consulta a API de Empresas:
\nGet:
https://bigboost.bigdatacorp.com.br/companies?
\nView=sua_view&
\nq=doc{xxxxxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"View\": \"sua_view\",
\n \"q\": \"doc{xxxxxxxxxxxxxx} \",
\n \"AccessToken\": \"\"
\n}
A API de Eventos permite que os desenvolvedores façam consultas em nossos logs utilizando o QueryId retornado por cada consulta.
\nO Manual de Integração do BigBoost é um guia simples que mostra como realizar a integração da nossa API com o\nback-end da sua empresa. Caso surjam dúvidas durante o processo, entre em contato diretamente com o nosso\nsuporte através do e-mail:
\nsupport.bigboost@bigdatacorp.com.br
\nAo realizar uma consulta o seu retorno é uma lista de status, onde cada status está ligado a um código. Cada objeto dentro da lista de status representa um dataset.
\nOs códigos que vão de -100 a -999 estão relacionados à problemas nos dados de entrada:
\nOs códigos que vão de -1000 até -1199 estão relacionados à problemas de login:
\nOs códigos que que vão de -1200 até -1999 estão relacionados à problemas nas APIs:
\nOs códigos que que vão de -2000 em diante estão relacionados às consultas on demand:
\nAo realizar uma consulta é possível escolher os parâmetros que deseja retornar em cada dataset. Os campos que são possíveis de selecionar estão disponíveis no JSON de retorno de cada dataset, vide os exemplos de retorno de cada um. O exemplo abaixo mostra uma chamada GET e POST selecionando apenas nome e data de nascimento no dataset 'Dados Básicos' para pessoas:
\nGet:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=basic_data{name, birthdate}&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"basic_data{name, birthdate}\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\"
\n}
Ao realizar qualquer consulta, é possível também passar uma data de referência como parâmetro, utilizando a data no formato yyyy-MM-dd (por exemplo, 2019-06-05). Essa data é usada como referência para as consultas realizadas na API ou através de back-testes, onde retorna os dados tais como estavam na data em questão.
\nExemplos de chamada GET e POST, utilizando uma data de refêrencia no dataset de 'Endereços' para pessoas:
\nGet:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=addresses&
\nq=doc{xxxxxxxxxxx},referencedate{2018-09-03}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"addresses\",
\n \"q\": \"doc{xxxxxxxxxxx},referencedate{2018-09-03}\",
\n \"AccessToken\": \"\"
\n}
Caso seja passada uma data inválida, será considerada a data atual como referência, o que equivale a uma consulta sem data de referência.
\n","event":[{"listen":"prerequest","script":{"id":"9f0fc1f5-4978-439e-9dd7-f736d26b77be","type":"text/javascript","exec":[""]}},{"listen":"test","script":{"id":"061b41a1-2b6d-441e-841e-908c11d91cd7","type":"text/javascript","exec":[""]}}],"_postman_id":"82fd516a-0283-4242-9468-0cfc5bf84f1f"},{"name":"Manual (en-US)","item":[{"name":"People API","item":[{"name":"Addresses","id":"31c3dd62-cfdc-4af9-ab54-18fd987cc2b8","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"addresses\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2","description":"This dataset returns data such as Detailed Address, Address Type, and Primary Address Indicator.
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=addresses.filter(type=work)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"addresses.filter(type=work)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
To use limit parameter, you can use the parameter .limit(x), shown in the example URL below:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets = addresses.limit(10) &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"addresses.limit(10)\",
\n \"q\": \"doc {xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as Name, CPF, and Mother Name.
\nBelow is the table that shows some fields and their returns:
\nThis dataset returns data such as Membership and Business Participation.
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=business_relationships.filter(RelationshipType=employment,CompanyFilters=headquarter)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"business_relationships.filter(RelationshipType=employment,CompanyFilters=headquarter)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
To use this limit, simply use the parameter .limit(x), shown in the example URL below:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets = business_relationships.limit(10) &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"business_relationships.limit(10)\",
\n \"q\": \"doc {xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data of neighbors which live in the same building as the searched person, as total related entities, age average and education level.
\nBelow is the table that shows some fields and their returns:
\nThis dataset returns data of Coworkers related to the searched person, as total related entities, age average and education level.
\nBelow is the table that shows some fields and their returns:
\nThis dataset returns data of college class related to the searched person, as total related entities, age average and education level.
\nBelow is the table that shows some fields and their returns:
\nThis dataset returns data of first level relatives of the searched person, as total related entities, age average and education level.
\nBelow is the table that shows some fields and their returns:
\nThis dataset returns data of people who participated in legal proceedings on the same side as the searched person, as total related entities, age average and education level.
\nBelow is the table that shows some fields and their returns:
\nThis dataset returns data of searched person's neighbors, as total related entities, age average and education level.
\nBelow is the table that shows some fields and their returns:
\nThis dataset returns data of Households related to the searched person, as total related entities, age average and education level.
\nBelow is the table that shows some fields and their returns:
\nThis dataset returns data of partners related to the searched person, as total related entities, age average and education level.
\nBelow is the table that shows some fields and their returns:
\nThis dataset returns data of relatives of the searched person, as total related entities, age average and education level.
\nBelow is the table that shows some fields and their returns:
\nThis dataset returns data such as Billing Presence Indicator, Billing Query Recurrence, and Billing Sources Quantity.
\nThis dataset returns data such as IBGE socio-demographic data and other sources.
\nBelow is the table that shows some fields and their returns:
\nThis dataset returns data such as Capture Data, Access Volume Data, and Structure Data.
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=domains.filter(framework=xxxxxxxx)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"domains.filter(framework=xxxxxxxx)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
To use this limit field, use the parameter .limit(x), shown in the example URL below:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets = domains.limit(10) &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"domains.limit(10)\",
\n \"q\": \"doc {xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as Email Address (es), Email Type, and Usage Indicators.
\nBelow is the table that shows some fields and their returns:
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=emails.filter(type=work)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"emails.filter(type=work)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
By default, this dataset will return 4 Emails Data. To increase this limit simply use the parameter .limit(x), shown in the example URL below:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets = emails.limit(10) &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"emails.limit(10)\",
\n \"q\": \"doc {xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Dataset which returns email addresses from related people.
\nOptional parameter
\n","urlObject":{"protocol":"https","path":["peoplev2"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"80c2630d-49a9-446d-aaba-ce76efbb401b","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/peoplev2?Datasets=related_people_emails&q=doc{xxxxxxxxxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["peoplev2"],"query":[{"key":"Datasets","value":"related_people_emails"},{"key":"q","value":"doc{xxxxxxxxxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"RelatedPeopleEmails\": [\n {\n \"EmailAddress\": \"teste@hotmail.com\",\n \"Domain\": \"hotmail.com\",\n \"UserName\": \"teste\",\n \"Type\": \"RELATED - xxxxxxxxxxx - BROTHER - personal\",\n \"EmailTotalPassages\": 1,\n \"EmailBadPassages\": 0,\n \"EmailCrawlingPassages\": -1,\n \"EmailValidationPassages\": -1,\n \"EmailQueryPassages\": -1,\n \"EmailMonthAveragePassages\": 1,\n \"EmailNumberOfEntities\": 2,\n \"Priority\": 1,\n \"IsMain\": true,\n \"IsRecent\": false,\n \"IsActive\": true,\n \"ValidationStatus\": \"VALID\",\n \"LastValidationDate\": \"2017-05-15T00:00:00Z\",\n \"FirstPassageDate\": \"2011-11-26T00:00:00Z\",\n \"LastPassageDate\": \"2011-11-26T00:00:00Z\",\n \"CreationDate\": \"2011-11-26T00:00:00Z\",\n \"LastUpdateDate\": \"2015-10-08T00:00:00Z\"\n }\n ]\n }\n ],\n \"QueryId\": \"a3e02f04-d49d-4cc7-83a0-98d42943bfcf\",\n \"ElapsedMilliseconds\": 793,\n \"Status\": {\n \"related_people_emails\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"a081bc08-82a8-4a5f-ad82-fefa96239e66","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"related_people_emails\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2"},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"RelatedPeopleEmails\": [\n {\n \"EmailAddress\": \"teste@hotmail.com\",\n \"Domain\": \"hotmail.com\",\n \"UserName\": \"teste\",\n \"Type\": \"RELATED - xxxxxxxxxxx - BROTHER - personal\",\n \"EmailTotalPassages\": 1,\n \"EmailBadPassages\": 0,\n \"EmailCrawlingPassages\": -1,\n \"EmailValidationPassages\": -1,\n \"EmailQueryPassages\": -1,\n \"EmailMonthAveragePassages\": 1,\n \"EmailNumberOfEntities\": 2,\n \"Priority\": 1,\n \"IsMain\": true,\n \"IsRecent\": false,\n \"IsActive\": true,\n \"ValidationStatus\": \"VALID\",\n \"LastValidationDate\": \"2017-05-15T00:00:00Z\",\n \"FirstPassageDate\": \"2011-11-26T00:00:00Z\",\n \"LastPassageDate\": \"2011-11-26T00:00:00Z\",\n \"CreationDate\": \"2011-11-26T00:00:00Z\",\n \"LastUpdateDate\": \"2015-10-08T00:00:00Z\"\n }\n ]\n }\n ],\n \"QueryId\": \"a3e02f04-d49d-4cc7-83a0-98d42943bfcf\",\n \"ElapsedMilliseconds\": 793,\n \"Status\": {\n \"related_people_emails\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"4e60a161-696e-4448-af42-96d699d678d5"},{"name":"Financial Data","id":"1cd136ad-5829-4c4f-a507-f9d99d4a4e7d","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"financial_data\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2","description":"This dataset returns data such as Estimated Income, Income Tax Return and Agency data and what bank the person has received the refund.
\nBelow is the table that shows some fields and their returns:
\nObs: SM -> Brazil's Minimum Wage
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=financial_data.filter(taxreturns_year=2015)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"financial_data.filter(taxreturns_year=2015)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as general Findability, Findability by email and Job Stability Indicator.
\nBelow is a table that looks at some fields and their returns:
\nHere are the model names and their possible descriptions:
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=flags_and_features.filter(modelinputkey=document)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"flags_and_features.filter(modelinputkey=document)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as Credit Card Usage Level, Participation in Mileage Programs, and Interest by Category.
\nBelow is the table that shows some fields and their returns:
\nAttention
\nIn this query you are charged per individual attribute within Dataset. If you want to select only a few attributes, you can use as shown below:
\nGet:
\nDatasets=interests_and_behaviors{SportAndLeisure,Housewares,CreditCardScore}
Post:
\n\"Datasets\"=\"interests_and_behaviors{SportAndLeisure,Housewares,CreditCardScore}\"
Below follow all the returned CategoriesOfInterest:
\n","urlObject":{"protocol":"https","path":["peoplev2"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"0eba56c3-f6b0-45da-9249-9fe0d50e0480","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/peoplev2?Datasets=interests_and_behaviors&q=doc{xxxxxxxxxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["peoplev2"],"query":[{"key":"Datasets","value":"interests_and_behaviors"},{"key":"q","value":"doc{xxxxxxxxxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"InterestsAndBehaviors\": {\n \"Behaviors\": {\n \"ProductReseller\": \"False\",\n\t\t \"CreditCardScore\": \"A\",\n\t\t \"MilesProgram\": \"False\",\n\t\t \"OnlineInvestor\": \"True\"\n },\n \"CategoriesOfInterest\": {\n \"Automotive\": 0,\n \"Baby\": 0,\n \"BeautyAndHealth\": 0,\n \"BeverageAndFood\": 0,\n \"Bodybuilding\": 0,\n \"Books\": 0,\n \"Computing\": 0,\n \"Delivery\": 0,\n \"Eletronics\": 0,\n \"Entertainment\": 0,\n \"FashionAndAcessories\": 0,\n \"Games\": 0.125,\n \"HomeAndDecoration\": 0,\n \"Housewares\": 0,\n \"MobileTelco\": 0,\n \"MusicalInstruments\": 0,\n \"Service\": 0,\n \"SportAndLeisure\": 0,\n \"Streaming\": 0,\n \"Toys\": 0,\n \"TravelAndTourism\": 0\n }\n }\n }\n ],\n \"QueryId\": \"ce928a4d-62b5-4817-8503-42abad08ae80\",\n \"ElapsedMilliseconds\": 145,\n \"Status\": {\n \"niches\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"dd6001e4-d94e-4571-bbe3-0604e51293f5","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"interests_and_behaviors\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2"},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"InterestsAndBehaviors\": {\n \"Behaviors\": {\n \"ProductReseller\": \"False\",\n\t\t \"CreditCardScore\": \"A\",\n\t\t \"MilesProgram\": \"False\",\n\t\t \"OnlineInvestor\": \"True\"\n },\n \"CategoriesOfInterest\": {\n \"Automotive\": 0,\n \"Baby\": 0,\n \"BeautyAndHealth\": 0,\n \"BeverageAndFood\": 0,\n \"Bodybuilding\": 0,\n \"Books\": 0,\n \"Computing\": 0,\n \"Delivery\": 0,\n \"Eletronics\": 0,\n \"Entertainment\": 0,\n \"FashionAndAcessories\": 0,\n \"Games\": 0.125,\n \"HomeAndDecoration\": 0,\n \"Housewares\": 0,\n \"MobileTelco\": 0,\n \"MusicalInstruments\": 0,\n \"Service\": 0,\n \"SportAndLeisure\": 0,\n \"Streaming\": 0,\n \"Toys\": 0,\n \"TravelAndTourism\": 0\n }\n }\n }\n ],\n \"QueryId\": \"ce928a4d-62b5-4817-8503-42abad08ae80\",\n \"ElapsedMilliseconds\": 145,\n \"Status\": {\n \"niches\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"757c0cf5-f76a-44cd-95ba-e1f9a4894228"},{"name":"KYC Information","id":"fd9185b5-650e-4a09-ad66-f988c5044ef3","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"kyc\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2","description":"This dataset returns data such as National PPE Indicator, Presence on terrorist lists and Presence in money laundering lists.
\nRequired Parameter
\nOptional Parameter
\nReturned values
\nBelow is a table that looks at some fields and their returns:
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=kyc.filter(type=[cnep,slavery])&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"kyc.filter(type=[cnep,slavery])\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as Media Exposure Indicator, Celebrity Level Indicator, and Unpopularity Indicator. The Exposure and Profile in the Media query accepts the following search parameters:
\nRequired Parameter
\nOptional Parameter
\nPagination: can be done using next parameter using page ID returned by each query as shown in the example bellow:
\nhttps://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=media_profile_and_exposure.next(page ID)&
\nq=&
\nAccessToken=
Below is a Get and Post call:
\nGet:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=media_profile_and_exposure&
\nq=name{your_name}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"media_profile_and_exposure\",
\n \"q\": \"name{your_name} \",
\n \"AccessToken\": \"\"
\n}
In this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=media_profile_and_exposure**.filter(sourcename=xxxxxxxx)**&
\nq=name{seu_nome}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"media_profile_and_exposure**.filter(sourcename=xxxxxxxx)**\",
\n \"q\": \"name{seu_nome} \",
\n \"AccessToken\": \"\"
\n}
By default, this dataset will return 4 Media profile and Exposure Data. To increase this limit simply use the parameter .limit(x), shown in the example URL below:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets = media_profile_and_exposure.limit(10) &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"media_profile_and_exposure.limit(10)\",
\n \"q\": \"doc {xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as Categories of products sold, Average value of product sold, and Category with the highest number of ads.
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
\nGet:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=online_ads.filter(totalads=10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"online_ads.filter(totalads=10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
To set the dataset limit, it is possible to simply use the parameter .limit(x), shown in the example URL below:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets = online_ads.limit(10) &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"online_ads.limit(10)\",
\n \"q\": \"doc {xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as Online Buyer Indicator, Internet usage level and Frequency of internet operations.
\nBelow is the table that shows some fields and their returns:
\nThis dataset returns data such as Phone Number (s), PROCON Indicator, and Primary Phone Indicator.
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=phones.filter(type=work)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"phones.filter(type=work)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
To this limit, simply use the parameter .limit(x), shown in the example URL below:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets = phones.limit(10) &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"phones.limit(10)\",
\n \"q\": \"doc {xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as Number of Processes, Total number of processes that a person has and Total number of processes that a person has as author.
\nBelow is the table that shows some fields and their returns:
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=processes.filter(state=rj)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"processes.filter(state=rj)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
To use this limit, simply use the parameter .limit(x), shown in the example URL below:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets = processes.limit(10) &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"processes.limit(10)\",
\n \"q\": \"doc {xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as Formal Profession, Informal Autonomous Work, and University Teachers.
\nIt's possible to use some filter parameters, as you can see at follow table:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=occupation_data.filter(companyname=xxxxxxxx)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"occupation_data.filter(companyname=xxxxxxxx)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as Class Counts and Class Entities, UF, and Activity Status.
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=class_organization.filter(status=ATIVO)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"class_organization.filter(status=ATIVO)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as Indicator and details of Public Server, Public Organization, and Remuneration.
\nIt's possible to use some filter parameters, as you can see at follow table:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=occupation_data.filter(companyname=xxxxxxxx)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"occupation_data.filter(companyname=xxxxxxxx)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as Relatives, Neighbors and Co-workers.
\nBelow is the table that shows some fields and their returns:
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=related_people.filter(relationshiptype=mother)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"related_people.filter(relationshiptype=mother)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
To use this limit, simply use the parameter .limit(x), shown in the example URL below:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets = related_people.limit(10) &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"related_people.limit(10)\",
\n \"q\": \"doc {xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as the \"Bolsa Família\" participation indicator.
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=social_assistance.filter(programstate=RJ)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"social_assistance.filter(programstate=RJ)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as University Student Indicator, CNPQ Details, and Medical Residency Details.
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=university_student_data.filter(level=undergraduate)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"university_student_data.filter(level=undergraduate)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
To use this limit field, use the parameter .limit(x), shown in the example URL below:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets = university_student_data.limit(10) &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"university_student_data.limit(10)\",
\n \"q\": \"doc {xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Dataset returns data referring to the vehicles related to the searched document.
\nBelow is a table that looks at some fields and their returns:
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=vehicles.filter(modelyear=2017)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"vehicles.filter(modelyear=2017)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
To use this limit, simply use the parameter .limit(x), shown in the example URL below:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets = vehicles.limit(10) &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"vehicles.limit(10)\",
\n \"q\": \"doc {xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as Frequency of passages through the web, Passage of the passage through the web and Frequency of suspicious passages through the web.
\nDataset which return phones from related people.
\nOptional parameter
\n","urlObject":{"protocol":"https","path":["peoplev2"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"59e503f0-5fae-4bf3-91c0-6588ce1a3539","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"related_people_phones\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2"},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"RelatedPeoplePhones\": [\n {\n \"Number\": \"32164715\",\n \"AreaCode\": \"91\",\n \"CountryCode\": \"55\",\n \"Complement\": \"\",\n \"Type\": \"WORK\",\n \"PhoneTotalPassages\": 84,\n \"PhoneBadPassages\": 0,\n \"PhoneCrawlingPassages\": 84,\n \"PhoneValidationPassages\": 0,\n \"PhoneQueryPassages\": -1,\n \"PhoneMonthAveragePassages\": 2,\n \"Priority\": 1,\n \"IsMain\": true,\n \"IsRecent\": false,\n \"IsActive\": false,\n \"IsInDoNotCallList\": false,\n \"CurrentCarrier\": \"\",\n \"PlanType\": \"\",\n \"FirstPassageDate\": \"2017-08-05T00:00:00Z\",\n \"LastPassageDate\": \"2017-08-17T00:00:00Z\",\n \"CreationDate\": \"2014-06-01T00:00:00Z\",\n \"LastUpdateDate\": \"2017-08-17T00:00:00Z\",\n \"PortabilityHistory\": [\n {\n \"OriginalCareer\": \"\",\n \"NewCareer\": \"\",\n \"PortabilityDate\": \"2017-11-18T00:00:00Z\"\n }\n ],\n \"HasOptIn\": false\n }\n ]\n }\n ],\n \"QueryId\": \"a3e02f04-d49d-4cc7-83a0-98d42943bfcf\",\n \"ElapsedMilliseconds\": 793,\n \"Status\": {\n \"related_people_addresses\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"63f775b2-b4be-4b88-a92e-f13092dd3d7c","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/peoplev2?Datasets=related_people_phones&q=doc{xxxxxxxxxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["peoplev2"],"query":[{"key":"Datasets","value":"related_people_phones"},{"key":"q","value":"doc{xxxxxxxxxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"RelatedPeoplePhones\": [\n {\n \"Number\": \"32164715\",\n \"AreaCode\": \"91\",\n \"CountryCode\": \"55\",\n \"Complement\": \"\",\n \"Type\": \"WORK\",\n \"PhoneTotalPassages\": 84,\n \"PhoneBadPassages\": 0,\n \"PhoneCrawlingPassages\": 84,\n \"PhoneValidationPassages\": 0,\n \"PhoneQueryPassages\": -1,\n \"PhoneMonthAveragePassages\": 2,\n \"Priority\": 1,\n \"IsMain\": true,\n \"IsRecent\": false,\n \"IsActive\": false,\n \"IsInDoNotCallList\": false,\n \"CurrentCarrier\": \"\",\n \"PlanType\": \"\",\n \"FirstPassageDate\": \"2017-08-05T00:00:00Z\",\n \"LastPassageDate\": \"2017-08-17T00:00:00Z\",\n \"CreationDate\": \"2014-06-01T00:00:00Z\",\n \"LastUpdateDate\": \"2017-08-17T00:00:00Z\",\n \"PortabilityHistory\": [\n {\n \"OriginalCareer\": \"\",\n \"NewCareer\": \"\",\n \"PortabilityDate\": \"2017-11-18T00:00:00Z\"\n }\n ],\n \"HasOptIn\": false\n }\n ]\n }\n ],\n \"QueryId\": \"a3e02f04-d49d-4cc7-83a0-98d42943bfcf\",\n \"ElapsedMilliseconds\": 793,\n \"Status\": {\n \"related_people_addresses\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"ad834db2-3326-4ed3-bfdd-165a8846c106"}],"id":"ed9abdd7-108e-4153-a1c6-b43b9b0527fe","description":"The People API encompasses all people-related queries. To perform queries it is necessary to fill in some parameters, which are shown in the table below:\n
The q parameter encompasses all search keys. When making a query by document (CPF) we recommend the search for CPF because it is more assertive and is always linked to only one person, not always our clients have the CPF to consult. Therefore, in addition to the CPF, BigBoost allows the user to query a series of additional parameters. Some of these parameters are arrays, so they accept more than one element delimited by comma. From the parameters below, one of them must be filled in to perform the searches for CPF assignment:\n
Besides these, we also have the optional parameters, which serve as filters to have a more assertive result:\n
The input parameters must be concatenated with a comma. The example below shows a query by name and date of birth. Keys can be combined according to the user's need.\n
Get:
\nq=name{your_name},birthdate{10/02/1995},dateformat{dd/MM/yyyy}
Post:
\n\"q\"=\"name{your_name},birthdate{10/02/1995},dateformat{dd/MM/yyyy}\"
For array objects e.g. phone, brackets can be used:
\nGet:
\nq=name{your_name},phone[21967654532,21976556234]
Post:
\n\"q\"=\"name{your_name},phone[21967654532,21976556234]\"
Keys can be combined according to the user's need. By default, the API will return only one person even if it finds more than one associated with the input information. To increase this limit simply use the Limit parameter, shown in the example URL below:\n
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=your_datasets&
\nq=name{your_name},birthdate{10/02/1995},dateformat{dd/MM/yyyy}&
\nAccessToken=&Limit=5
Post:
Body:
\n{
\n \"Datasets\": \"your_datasets\",
\n \"q\": \"name{your_name},birthdate{10/02/1995},dateformat{dd/MM/yyyy} \",
\n \"AccessToken\": \"\",
\n \"Limit\"=\"5\"
\n}
CAUTION: The cost of the query is for each dataset queried, that is, if we find 2 people and enrich with a dataset, the price to be paid will be the value of this dataset times the 2 enriched people.\n
The Datasets parameter considers the entire set of data that should be used for the query. Below we list the datasets available in the People API:\n
The name of the datasets must be separated by commas within the Datasets parameter. If you want query for basic data, telephones and e-mails for example, the parameter Datasets must be completed from the following way:\n
Because the selected dataset list can be very large, you can associate this set of datasets with a view through our Views API. A view is an alias for a set of datasets. If you choose to create a view, direct your reading to the session ** Views API **.
\n","event":[{"listen":"prerequest","script":{"id":"29531317-3428-4450-8565-27c06e7edbc1","type":"text/javascript","exec":[""]}},{"listen":"test","script":{"id":"ddc6d43f-b5d0-4691-bdd5-00585358501d","type":"text/javascript","exec":[""]}}],"_postman_id":"ed9abdd7-108e-4153-a1c6-b43b9b0527fe"},{"name":"Companies API","item":[{"name":"Activity Indicators","id":"16fb94da-d35a-40ac-866c-9c8e88701d16","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"activity_indicators\",\r\n\t\"q\": \"doc{xxxxxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/companies","description":"Este dataset retorna dados tais como Atividade operacional, Número de funcionários e Faturamento estimado.
\nBelow is the table that shows some fields and their returns:
\nThis dataset returns data such as Detailed Address, Address Type, and Usage Indicators.
\nBelow is the table that shows some fields and their returns:
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=addresses.filter(type=work)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"addresses.filter(type=work)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
By default, this dataset will return 4 data records. To increase this limit simply use the parameter .limit(x), shown in the example URL below:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/companies?
\nDatasets = addresses.limit(10) &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"addresses.limit(10)\",
\n \"q\": \"doc {xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as Corporate Name, CNPJ and Status in \"Receita Federal\".
\nBelow is the table that shows some fields and their returns:
\nThis dataset returns data such as Classification Data, Basic Technology Data, and Social Media Integration Data.
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=domains.filter(framework=xxxxxxxx)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"domains.filter(framework=xxxxxxxx)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
To use this limit, simply use the parameter .limit(x), shown in the example URL below:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/companies?
\nDatasets = domains.limit(10) &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"domains.limit(10)\",
\n \"q\": \"doc {xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Below is the table that shows some fields and their returns:
\nTo use this limit, simply use the parameter .limit(x), shown in the example URL below:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/companies?
\nDatasets = economic_group_data.limit(10) &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"economic_group_data.limit(10)\",
\n \"q\": \"doc {xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as E-mail Address (es), Frequency Indicators, and Usage Indicators.
\nBelow is the table that shows some fields and their returns:
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=emails.filter(type=work)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"emails.filter(type=work)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
By default, this dataset will return 4 data records. To increase this limit simply use the parameter .limit(x), shown in the example URL below:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/companies?
\nDatasets = emails.limit(10) &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"emails.limit(10)\",
\n \"q\": \"doc {xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
Parameter required
\nOptional parameter
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=kyc.filter(sanctions_source=interpol)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"kyc.filter(sanctions_source=interpol)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as Media Exposure Indicator, Celebrity Level Indicator, and Unpopularity Indicator.
\nThe Exposure and Profile in the Media query accepts the following search parameters:
\nRequired Parameter
\nOptional Parameter
\nPagination: can be done using next parameter using page ID returned by each query as shown in the example bellow:
\nhttps://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=media_profile_and_exposure.next(page ID)&
\nq=&
\nAccessToken=
Below is a Get and Post call:
\nGet:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=media_profile_and_exposure&
\nq=name{company_name}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"media_profile_and_exposure\",
\n \"q\": \"name{company_name} \",
\n \"AccessToken\": \"\"
\n}
In this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=media_profile_and_exposure**.filter(sourcename=xxxxxxxx)**&
\nq=name{seu_nome}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"media_profile_and_exposure**.filter(sourcename=xxxxxxxx)**\",
\n \"q\": \"name{seu_nome} \",
\n \"AccessToken\": \"\"
\n}
This dataset returns data such as Product categories sold, Average value of product sold, and Average number of ads in the last \"n\" days.
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=online_ads.filter(totalads=10)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"online_ads.filter(totalads=10)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
To use this limit, simply use the parameter .limit(x), shown in the example URL below:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/companies?
\nDatasets = online_ads.limit(10) &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"online_ads.limit(10)\",
\n \"q\": \"doc {xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as Phone Number (s), Phone Type, and Frequency Indicators.
\nBelow is the table that shows some fields and their returns:
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=phones.filter(type=work)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"phones.filter(type=work)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
To use this limit, simply use the parameter .limit(x), shown in the example URL below:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/companies?
\nDatasets = phones.limit(10) &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"phones.limit(10)\",
\n \"q\": \"doc {xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as Number of Processes, Total number of processes that a company has and Total number of processes that a company has as author.
\nBelow is the table that shows some fields and their returns:
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=processes.filter(state=rj)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"processes.filter(state=rj)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
By default, this dataset will return 4 data records. To increase this limit simply use the parameter .limit(x), shown in the example URL below:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/companies?
\nDatasets = processes.limit(10) &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"processes.limit(10)\",
\n \"q\": \"doc {xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
This dataset returns data such as Partners (people or companies), Employees and Participation in companies.
\nBelow is the table that shows some fields and their returns:
\nIn this dataset you can filter some fields, which are shown in the table below along with the parameters that are accepted as filters:
\nHere is an example of how to use the filter(field_name=xxxx) parameter, shown in the example URL in the GET and POST methods:
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=relationships.filter(relationshiptype=employee)&
\nq=doc{xxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"relationships.filter(relationshiptype=employee)\",
\n \"q\": \"doc{xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
By default, this dataset will return 4 data records. To increase this limit simply use the parameter .limit(x), shown in the example URL below:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/companies?
\nDatasets = relationships.limit(10) &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"relationships.limit(10)\",
\n \"q\": \"doc {xxxxxxxxxxx}\",
\n \"AccessToken\": \"\",
\n}
The Companies API encompasses all business-related queries. To perform queries it is necessary to fill in some parameters, which are shown in the table below:
The q parameter encompasses all search keys. When making a query by document (CNPJ) we recommend the search for CNPJ because it is more assertive and always is linked to only one company, but not always our clients have the CNPJ to consult. Therefore, in addition to CNPJ, BigBoost allows the user to query a series of additional parameters. Some of these parameters are array, so they accept more than one element delimited by commas. From the parameters below, one of them must be filled in to perform the searches for CNPJ assignment:
Besides these, we also have the optional parameters, which serve as filters to have a more assertive result:\n
The input parameters must be concatenated with a comma. The array objects can also be used with brackets. Below we show a combination of these parameters with a query by name, phone and email:\n
Get:
\nq=name{company_name},phone[xxxx,xxxx],email[company_email@email.com]
Post:
\n\"q\"=\"name{company_name},phone[xxxx,xxxx],email[company_email@email.com]\"
Keys can be combined according to the user's need. By default, the API will return only one company even if it finds more than one associated with the input information. To increase this limit simply use the Limit parameter, shown in the example URL below:\n
Get:
https://bigboost.bigdatacorp.com.br/companies?
\nDatasets=seus_datasets&
\nq=name{company_name},email{company_email@email.com}&
\nAccessToken=&Limit=5
Post:
Body:
\n{
\n \"Datasets\": \"seus_datasets\",
\n \"q\": \"name{company_name},email{company_email@email.com} \",
\n \"AccessToken\": \"\",
\n \"Limit\"=\"5\"
\n}
CAUTION: the cost of the query is for each dataset consulted, that is, if we find 2 companies and enrich with a dataset, the price to be paid will be the value of this dataset times the 2 enriched companies.\n
The Datasets parameter considers the entire set of data that should be used for the query. Below we list the datasets made available in the Companies API:\n
The name of the datasets must be separated by commas within the 'Datasets' parameter. If you want to query for basic data, telephones and e-mails for example, the parameter Datasets must be completed in the following way:\n
Because the selected dataset list can be very large, you can associate this set of datasets with a view through our Views API. A view is an alias for a set of datasets. If you choose to create a view, direct your reading to the session Views API.
\n","event":[{"listen":"prerequest","script":{"id":"8e14c67e-3e79-424d-91ef-fe5e313f07e8","type":"text/javascript","exec":[""]}},{"listen":"test","script":{"id":"df681d1c-4c75-4363-9c74-ee5c74a5c525","type":"text/javascript","exec":[""]}}],"_postman_id":"f5424691-7ab0-4b18-821b-142e2be04adf"},{"name":"Misc API","item":[{"name":"E-Mail Statistics","id":"f7d9f54e-3a77-44a5-82a6-383134f9b942","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"statistics_email\",\r\n\t\"q\": \"email{seu_email@email.com.br}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/misc","description":"Dataset return statics from searched email.
\nValid categories: \"CARROS\" (cars), \"CAMINHOES\" (trucks) and \"MOTOS\" (motorcycles)
\n","urlObject":{"protocol":"https","path":["misc"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"2fae0db4-756a-4705-b648-8d2977ac9964","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","name":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/misc?Datasets=fipe_brands&q=category{xxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["misc"],"query":[{"key":"Datasets","value":"fipe_brands"},{"key":"q","value":"category{xxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"FipeBrands\": [\n {\n \"Brand\": \"ACURA\"\n },\n {\n \"Brand\": \"AGRALE\"\n },\n {\n \"Brand\": \"ALFA ROMEO\"\n },\n {\n \"Brand\": \"AM GEN\"\n },\n {\n \"Brand\": \"ASIA MOTORS\"\n },\n {\n \"Brand\": \"ASTON MARTIN\"\n },\n {\n \"Brand\": \"AUDI\"\n }\n ]\n }\n ],\n \"QueryId\": \"25e6cb50-10d7-4249-b94d-c52f4db65691\",\n \"ElapsedMilliseconds\": 3187,\n \"Status\": {\n \"fipe_brands\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"b02452bc-64fa-47f7-a6ce-9abca50a47f4","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"fipe_brands\",\r\n\t\"q\": \"category{xxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/misc"},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"FipeBrands\": [\n {\n \"Brand\": \"ACURA\"\n },\n {\n \"Brand\": \"AGRALE\"\n },\n {\n \"Brand\": \"ALFA ROMEO\"\n },\n {\n \"Brand\": \"AM GEN\"\n },\n {\n \"Brand\": \"ASIA MOTORS\"\n },\n {\n \"Brand\": \"ASTON MARTIN\"\n },\n {\n \"Brand\": \"AUDI\"\n }\n ]\n }\n ],\n \"QueryId\": \"25e6cb50-10d7-4249-b94d-c52f4db65691\",\n \"ElapsedMilliseconds\": 3187,\n \"Status\": {\n \"fipe_brands\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"1516de12-078f-42b8-abc8-88add7f57920"},{"name":"Fipe - 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\nMisc datasets are data sets that are not tightly tied to people or companies, and usually associate with other entities. These data can serve as alternative sources of generation of derived attributes for modeling processes, or they can be used in their natural context for the construction of artificial intelligence models.
\n","event":[{"listen":"prerequest","script":{"id":"f7de09b9-1bb4-40c0-9ed3-b711145a5306","type":"text/javascript","exec":[""]}},{"listen":"test","script":{"id":"23dff383-3739-402d-beb6-3ca27771dbc5","type":"text/javascript","exec":[""]}}],"_postman_id":"724e2514-cd99-4731-bb10-7210239a7b7f"},{"name":"On Demand API ","item":[{"name":"People API","item":[{"name":"Boa Vista (with Score)","id":"3c8fff6a-d128-4251-88d3-3c600d268c0d","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"ondemand_credit_boavista_score\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2","description":"Data referring to the registration of the CPF in COAF (Council for Control of Financial Activities).
\nThe query Certificate of \"Nada Consta\" accepts the following search parameters:
\nRequired Parameter
\nOptional Parameters
\nFor the optional parameters the following arguments are accepted:
\ncourt: TRF1 / TRF2 / TRF3 / TRF4 / TRF5.
\nop: CIVIL / CRIMINAL.
\nThis dataset returns information of \"Procuradoria-Geral da Fazenda Nacional\" (Attorney General of the National Treasury)
\nWhen passing the date of birth, one must also pass the format in which the date of birth is being sent in the requisition. For example:
\nGet:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=ondemand_rf_status&
\nq=doc{xxxxxxxxxxx},birthdate{10-07-1998},dateformat{dd-MM-yyyy}\n&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"ondemand_rf_status\",
\n \"q\": \"doc{xxxxxxxxxxx},birthdate{10-07-1998},dateformat{dd-MM-yyyy}\",
\n \"AccessToken\": \"\",
\n}
The \"Rais\" query accepts the following search parameter
\nRequired Parameter
\nOptional Parameter
\n","urlObject":{"protocol":"https","path":["peoplev2"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"630fc63d-07b3-42d9-bf5f-28d1834598a8","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"ondemand_cert_rais\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2"},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"OnlineQuery\": [\n {\n \"Origin\": \"Rais\",\n \"InputParameters\": \"doc{xxxxxxxxxxx}\",\n \"AdditionalOutputData\": {\n \"Name\": \"ANA KELEN DE CARVALHO\",\n \"Nit\": \"13098383274\",\n \"IdNumber.0\": \"\",\n \"OfficialName.0\": \"ESSENCE TERC MAO OBRA E SERVICOS LTDA\",\n \"Cnpj/Caepf/Cei/Cno.0\": \"06.290.395/0001-90\",\n \"DeliveryStatus.0\": \"ENTREGUE\",\n \"DtDelivery.0\": \"2018-03-22\",\n \"DtAdimission.0\": \"2016-09-01\"\n },\n \"QueryDate\": \"2019-03-27T20:33:08.8578526Z\"\n }\n ]\n }\n ],\n \"QueryId\": \"30a39d94-5739-43ac-aa60-6da44841c3c7\",\n \"ElapsedMilliseconds\": 1130,\n \"Status\": {\n \"ondemand_rais\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"d11cadff-58c8-4286-a21a-6e31dd61cd34","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/peoplev2?Datasets=ondemand_cert_rais&q=doc{xxxxxxxxxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["peoplev2"],"query":[{"key":"Datasets","value":"ondemand_cert_rais"},{"key":"q","value":"doc{xxxxxxxxxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"OnlineQuery\": [\n {\n \"Origin\": \"Rais\",\n \"InputParameters\": \"doc{xxxxxxxxxxx}\",\n \"AdditionalOutputData\": {\n \"Name\": \"ANA KELEN DE CARVALHO\",\n \"Nit\": \"13098383274\",\n \"IdNumber.0\": \"\",\n \"OfficialName.0\": \"ESSENCE TERC MAO OBRA E SERVICOS LTDA\",\n \"Cnpj/Caepf/Cei/Cno.0\": \"06.290.395/0001-90\",\n \"DeliveryStatus.0\": \"ENTREGUE\",\n \"DtDelivery.0\": \"2018-03-22\",\n \"DtAdimission.0\": \"2016-09-01\"\n },\n \"QueryDate\": \"2019-03-27T20:33:08.8578526Z\"\n }\n ]\n }\n ],\n \"QueryId\": \"30a39d94-5739-43ac-aa60-6da44841c3c7\",\n \"ElapsedMilliseconds\": 1130,\n \"Status\": {\n \"ondemand_rais\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"bbccf3e3-d375-44de-b82a-7733d5af3923"},{"name":"\"Seguro Desemprego\" ","id":"3eb6018a-618a-48bd-a284-81859f0aa02e","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"ondemand_seguro_desemprego\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2","description":"The \"Seguro Desemprego\" query accepts the following search parameter
\nRequired Parameter
\nOptional Parameter
\n","urlObject":{"protocol":"https","path":["peoplev2"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"0124f1de-4b2f-4110-a604-1f27798d7972","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/peoplev2?Datasets=ondemand_seguro_desemprego&q=doc{xxxxxxxxxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["peoplev2"],"query":[{"key":"Datasets","value":"ondemand_seguro_desemprego"},{"key":"q","value":"doc{xxxxxxxxxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"OnlineQuery\": [\n {\n \"Origin\": \"SeguroDesemprego\",\n \"InputParameters\": \"doc{xxxxxxxxxxx}\",\n \"QueryResultData\": {\n \"Name\": \"ALEXSANDRA CARDOSO DE MORAES\",\n \"NitNumber\": \"12615713673\",\n \"InsuranceStatus\": \"NOTIFICADO\",\n \"PeriodOfEmployment\": \"11 MESES\",\n \"Procedure\": \"PREZADO SR(A). POR GENTILEZA PROCURE UM POSTO DO SINE OU CONVENIADO O QUAL FEZ O SEU CADASTRO PARA ACOES DE EMPREGO E SOLICITE SEU HISTORICO E EM SEGUIDA DIRIJA-SE A UM POSTO DO MINISTERIO DO TRABALHO E EMPREGO COM A SEGUINTE DOCUMENTACAO: -CARTEIRA DE TRABALHO; -FORMULARIO DO SEGURO-DESEMPREGO (VIA MARROM); -RESCISAO DO CONTRATO DE TRABALHO; -HISTORICO DO TRABALHADOR FORNECIDO PELO SINE.\",\n \"Reason\": \"MAIS DE 02 ANOS DA DATA DE DEMISSAO/SUSPENSAO\"\n },\n \"QueryDate\": \"2019-03-27T19:35:37.4264939Z\"\n }\n ]\n }\n ],\n \"QueryId\": \"ffe8e729-6935-4edf-a3d6-8e4c101422ac\",\n \"ElapsedMilliseconds\": 18616,\n \"Status\": {\n \"ondemand_seguro_desemprego\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"08d5641c-0d4d-438c-99c4-db07c5095917","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"ondemand_seguro_desemprego\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2"},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"OnlineQuery\": [\n {\n \"Origin\": \"SeguroDesemprego\",\n \"InputParameters\": \"doc{xxxxxxxxxxx}\",\n \"QueryResultData\": {\n \"Name\": \"ALEXSANDRA CARDOSO DE MORAES\",\n \"NitNumber\": \"12615713673\",\n \"InsuranceStatus\": \"NOTIFICADO\",\n \"PeriodOfEmployment\": \"11 MESES\",\n \"Procedure\": \"PREZADO SR(A). POR GENTILEZA PROCURE UM POSTO DO SINE OU CONVENIADO O QUAL FEZ O SEU CADASTRO PARA ACOES DE EMPREGO E SOLICITE SEU HISTORICO E EM SEGUIDA DIRIJA-SE A UM POSTO DO MINISTERIO DO TRABALHO E EMPREGO COM A SEGUINTE DOCUMENTACAO: -CARTEIRA DE TRABALHO; -FORMULARIO DO SEGURO-DESEMPREGO (VIA MARROM); -RESCISAO DO CONTRATO DE TRABALHO; -HISTORICO DO TRABALHADOR FORNECIDO PELO SINE.\",\n \"Reason\": \"MAIS DE 02 ANOS DA DATA DE DEMISSAO/SUSPENSAO\"\n },\n \"QueryDate\": \"2019-03-27T19:35:37.4264939Z\"\n }\n ]\n }\n ],\n \"QueryId\": \"ffe8e729-6935-4edf-a3d6-8e4c101422ac\",\n \"ElapsedMilliseconds\": 18616,\n \"Status\": {\n \"ondemand_seguro_desemprego\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"3eb6018a-618a-48bd-a284-81859f0aa02e"},{"name":"SPC Brasil (with Score)","id":"6a67ffea-494c-4458-ae57-1c7e15dbfc75","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"ondemand_credit_spc_score_12_months\",\r\n\t\"q\": \"doc{xxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/peoplev2","description":"The SPC credit query with score allows 2 query models: score in relation to the last 3 months and in relation to the last 12 months:
\n","urlObject":{"protocol":"https","path":["peoplev2"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"40f2d9a5-de80-4f0e-b43a-cd0e70e88e97","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/peoplev2?Datasets=ondemand_credit_spc_score_12_months&q=doc{xxxxxxxxxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["peoplev2"],"query":[{"key":"Datasets","value":"ondemand_credit_spc_score_12_months"},{"key":"q","value":"doc{xxxxxxxxxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxx}\",\n \"CreditData\": [\n {\n \"Origin\": \"SPC\",\n \"QueryDate\": \"2018-08-13T00:00:00\",\n \"BasicData\": {\n \"TaxIdNumber\": \"xxxxxxxxxxx\",\n \"TaxIdCountry\": \"Brazil\",\n \"AlternativeIdNumbers\": {\n \"VoterRegistration\": \"\"\n },\n \"Name\": \"GHERSON CASTRO\",\n \"Gender\": \"M\",\n \"BirthDate\": \"1966-03-31T00:00:00\",\n \"Age\": 52,\n \"ZodiacSign\": \"ARIES\",\n \"MotherName\": \"HELVIA DA SILVA TAVARES FRANCA\",\n \"TaxIdStatus\": \"SUSPENSA\",\n \"TaxIdOrigin\": \"SPC\"\n },\n \"PersonalRelationships\": [\n {\n \"RelatedEntityName\": \"HELVIA DA SILVA TAVARES FRANCA\",\n \"RelationshipType\": \"MOTHER\",\n \"RelationshipLevel\": \"DIRECT\"\n }\n ],\n \"Emails\": [\n {\n \"EmailAddress\": \"email@email.com.br\"\n }\n ],\n \"Phones\": [\n \t\t{\n\t \"Number\": \"32166540\",\n\t \"AreaCode\": \"11\",\n\t \"CountryCode\": \"55\",\n\t \"HasOptIn\": false\n\t },\n\t {\n\t \"Number\": \"33715971\",\n\t \"AreaCode\": \"11\",\n\t \"CountryCode\": \"55\",\n\t \"HasOptIn\": false\n\t },\n\t {\n\t \"Number\": \"32133213\",\n\t \"AreaCode\": \"47\",\n\t \"CountryCode\": \"55\",\n\t \"HasOptIn\": false\n\t }\n \t],\n \"Addresses\": [\n {\n \"AddressMain\": \"R HUMBERTO CAMPOS\",\n \"Number\": \"000537\",\n \"Complement\": \"\",\n \"Neighborhood\": \"CHACARA\",\n \"ZipCode\": \"32670300\",\n \"City\": \"BETIM\",\n \"State\": \"MG\",\n \"Country\": \"Brazil\"\n },\n {\n \"AddressMain\": \"R HUMBERTO CAMPOS 137\",\n \"Number\": \"\",\n \"Complement\": \"\",\n \"Neighborhood\": \"CHACARA\",\n \"ZipCode\": \"32670900\",\n \"City\": \"BETIM\",\n \"State\": \"MG\",\n \"Country\": \"Brazil\"\n }\n ],\n \"TotalDebts\": 1556.88,\n \"TotalCount\": 5,\n \"TotalPreviousQueries\": 56,\n \"PreviousQueries\": [\n {\n \"Origin\": \"SERASA EXPERIAN\",\n \"QueryDate\": \"2019-03-27T00:00:00\",\n \"Name\": \"SEGUROS NAOVIDA\",\n \"CityAndState\": {\n \"City\": \"SAO PAULO\",\n \"State\": \"SP\"\n }\n },\n {\n \"Origin\": \"CDL - 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\nThis dataset returns information of \"Procuradoria-Geral da Fazenda Nacional\" (Attorney General of the National Treasury)
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\n","urlObject":{"protocol":"https","path":["companies"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"940da0ec-7cc9-4e41-b8dd-0722f1c99e5a","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Datasets\": \"ondemand_credit_spc_score_12_months\",\r\n\t\"q\": \"doc{xxxxxxxxxxxxxx}\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/companies"},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"MatchKeys\": \"doc{xxxxxxxxxxxxxx}\",\n \"CreditData\": [\n {\n \"Origin\": \"SPC\",\n \"QueryDate\": \"2018-08-13T00:00:00\",\n \"BasicData\": {\n \"TaxIdNumber\": \"xxxxxxxxxxxxxx\",\n\t\t\t\t \"TaxIdCountry\": \"Brazil\",\n\t\t\t\t \"AlternativeIdNumbers\": {\n\t\t\t\t \n\t\t\t\t },\n\t\t\t\t \"OfficialName\": \"EMPORIO VIRADAO MERCEARIA E CONVENIENCIA EIRELI\",\n\t\t\t\t \"TradeName\": \"MINI MERCADO EMPORIO VIRADAO\",\n\t\t\t\t \"FoundedDate\": \"2016-07-19T00:00:00\",\n\t\t\t\t \"Age\": 2.0,\n\t\t\t\t \"TaxIdStatus\": \"ATIVA\",\n\t\t\t\t \"TaxIdOrigin\": \"SPC\",\n\t\t\t\t \"Activities\": [\n\t\t\t\t {\n\t\t\t\t \"IsMain\": true,\n\t\t\t\t \"Code\": \"4729602\",\n\t\t\t\t \"Activity\": \"COMERCIO VAREJISTA DE MERCADORIAS EM LOJAS DE CONVENIENCIA\"\n\t\t\t\t }\n\t\t\t\t ],\n\t\t\t\t \"LegalNature\": {\n\t\t\t\t \"Code\": \"2305\",\n\t\t\t\t \"Activity\": \"EMPRESA INDIVIDUAL DE RESPONSABILIDADE LIMITADA DE NATUREZA EMPRESARIA\"\n\t\t\t\t },\n\t\t\t\t \"AdditionalOutputData\": {\n\t\t\t\t \"Spelling_0\": \"MERCEARIA DO PIERRY EIRELI ME\",\n\t\t\t\t \"Spelling_1\": \"EMPORIO VIRADAO MERCEARIA E CONVENIENCIA EIRELI\"\n\t\t\t\t }\n },\n \"Emails\": [\n\t \t{\n\t \t\t\"EmailAddress\": \"joao@joape.com.br\"\n\t \t}\n \t],\n \"Phones\": [\n\t \t{\n\t\t\t\t\t \"Number\": \"993418933\",\n\t\t\t\t\t \"AreaCode\": 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}\n}"},{"id":"95242c7c-87b9-43c0-8cca-1931f4d02d2b","name":"GET","originalRequest":{"method":"GET","header":[{"key":"Content-Type","value":"application/json"}],"url":{"raw":"https://bigboost.bigdatacorp.com.br/validations?Datasets=ondemand_phone_operator&q=phone{xxxxxxxxxxx}&AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["validations"],"query":[{"key":"Datasets","value":"ondemand_phone_operator"},{"key":"q","value":"phone{xxxxxxxxxxx}"},{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": [\n {\n \"OnlineCertificates\": [\n {\n \"Origin\": \"ABRT\",\n \"InputParameters\": \"phone{2132513142}\",\n \"NormalizedInputs\": \"phone{2132513142}\",\n \"ValidationType\": \"Phone Operator\",\n \"MainValidationStatus\": \"VALID\",\n \"AdditionalValidationDetails\": {\n \"OfficialName\": \"EMPRESA BRASILEIRA DE TELECOMUNICACOES S. A.\",\n \"BusinessName\": \"Embratel\",\n \"LastUpdateDate\": \"27/03/2019\",\n \"LastUpdateTime\": \"16:39\"\n },\n \"QueryDate\": \"2019-03-27T19:39:31.0625311Z\"\n }\n ]\n }\n ],\n \"QueryId\": \"84bea04b-dcd6-4d17-9c23-ee2ecdbb7bbf\",\n \"ElapsedMilliseconds\": 5020,\n \"Status\": {\n \"ondemand_phone_portability\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"81ad3823-8cea-4f06-8e6d-935b59b2c299"}],"id":"245650b8-9aed-48b9-80cd-9cc68cd6f291","event":[{"listen":"prerequest","script":{"id":"36ab1cd4-7ea3-4576-a3a7-859c73cda582","type":"text/javascript","exec":[""]}},{"listen":"test","script":{"id":"a027757e-04f4-4091-baa3-ff038bbc95c8","type":"text/javascript","exec":[""]}}],"_postman_id":"245650b8-9aed-48b9-80cd-9cc68cd6f291","description":""}],"id":"4fddc673-d15d-4bd0-9573-49a1a19afce0","description":"On Demand services are queries executed in real-time, for which it is neither technically nor viable to maintain offline bases and data history of what was consulted. All services listed here are available for API call separately from the other data.
\nThe detail call allows the user to visualize all views that are associated with his AccessToken. The result node contains a list with all associated views as well as the description of each.
\n","urlObject":{"protocol":"https","path":["views","Details"],"host":["bigboost","bigdatacorp","com","br"],"query":[],"variable":[]}},"response":[{"id":"a9d35497-26ef-4e98-af0a-9e521bd2c488","name":"POST","originalRequest":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"AccessToken\": \"\"\r\n}\r\n\r\n"},"url":"https://bigboost.bigdatacorp.com.br/views/Details"},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": {\n \"view_name_1\": {\n \"CreationDate\": \"2018-09-03T21:19:52.7162586Z\",\n \"LastUpdateDate\": \"2018-09-04T18:39:15.1957757Z\",\n \"Api\": \"People\",\n \"Datasets\": \"basic_data,emails\"\n },\n \"view_name_2\": {\n \"CreationDate\": \"2018-09-04T19:01:22.2353159Z\",\n \"LastUpdateDate\": \"2018-09-04T19:01:22.2353159Z\",\n \"Api\": \"Companies\",\n \"Datasets\": \"basic_data,phones,addresses\"\n }\n },\n \"QueryId\": \"253d6ab1-d620-4518-b9b8-9e516477bc0f\",\n \"ElapsedMilliseconds\": 20,\n \"Status\": {\n \"api\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"},{"id":"b50a0cde-b43d-4227-9b21-646605a8a9a1","name":"GET","originalRequest":{"method":"GET","header":[],"url":{"raw":"https://bigboost.bigdatacorp.com.br/views/Details?AccessToken=","protocol":"https","host":["bigboost","bigdatacorp","com","br"],"path":["views","Details"],"query":[{"key":"AccessToken","value":""}]}},"status":"OK","code":200,"_postman_previewlanguage":"json","header":[],"cookie":[],"responseTime":null,"body":"{\n \"Result\": {\n \"view_name_1\": {\n \"CreationDate\": \"2018-09-03T21:19:52.7162586Z\",\n \"LastUpdateDate\": \"2018-09-04T18:39:15.1957757Z\",\n \"Api\": \"People\",\n \"Datasets\": \"basic_data,emails\"\n },\n \"view_name_2\": {\n \"CreationDate\": \"2018-09-04T19:01:22.2353159Z\",\n \"LastUpdateDate\": \"2018-09-04T19:01:22.2353159Z\",\n \"Api\": \"Companies\",\n \"Datasets\": \"basic_data,phones,addresses\"\n }\n },\n \"QueryId\": \"253d6ab1-d620-4518-b9b8-9e516477bc0f\",\n \"ElapsedMilliseconds\": 20,\n \"Status\": {\n \"api\": [\n {\n \"Code\": 0,\n \"Message\": \"OK\"\n }\n ]\n }\n}"}],"_postman_id":"64b83801-6ba2-4fbf-95c9-cefc5a4c7a90"},{"name":"Update","id":"1ba81fa8-23a3-4ff0-9618-11844b6a8590","protocolProfileBehavior":{"disableBodyPruning":true},"request":{"method":"POST","header":[{"key":"Content-Type","value":"application/json"}],"body":{"mode":"raw","raw":"{\r\n\t\"Api\": \"api_name\",\r\n\t\"Datasets\": \"your_dataset1,your_dataset2,your_dataset3\",\r\n\t\"View\": \"your_view\",\r\n\t\"AccessToken\": \"\"\r\n}"},"url":"https://bigboost.bigdatacorp.com.br/views/Update","description":"The Views API allows you to save a set of datasets for use in the other query APIs. The advantage of creating a view is that once it is created, the user will no longer need to inform the set of datasets in the enrichment URL since they will already be associated with the view.
\nTo perform queries using Views you need to fill in some parameters that are shown in the table below:
\nA view acts as an alias for a data set, where all calls are made through HTTP / HTTPS requests via Get or Post. Below is an example of the URL format that should be used for a Get and Post call for a Companies API query:
\nGet:
https://bigboost.bigdatacorp.com.br/companies?
\nView=your_view&
\nq=doc{xxxxxxxxxxxxxx}&
\nAccessToken=
Post:
Body:
\n{
\n \"View\": \"your_view\",
\n \"q\": \"doc{xxxxxxxxxxxxxx} \",
\n \"AccessToken\": \"\"
\n}
Events API allows developers to query our logs using QueryId parameter returned by each query made by them.
\nThe BigBoost Integration Guide is a simple guide that shows how to integrate our API with the back-end of your business. If you have any questions during the process, please contact our support via email:
\nsupport.bigboost@bigdatacorp.com.br
\nWhen performing a query your return is a status list, where each status is linked to a code. Each object within the status list represents a dataset.
\nCodes ranging from -100 to -999 are related to problems in the input data:
\nCodes ranging from -1000 to -1199 are related to login issues:
\nCodes ranging from -1200 to -1999 are related to API issues:
\nCodes that range from -2000 onwards are related to on demand queries:
\nWhen performing a query it is possible to choose the parameters that you want to return in each dataset. The fields that are possible to select are available in the return JSON of each dataset, see the return examples for each. The example below shows a GET and POST call by selecting only name and date of birth in the dataset 'Basic Data' for people:
\nGet:
\nhttps://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets = basic_data{name, birthdate} &
\nq = doc{xxxxxxxxxxx} &
\nAccessToken =
Post:
Body:
\n{
\n \"Datasets\": \"basic_data{name, birthdate}\",
\n \"q\": \"doc{xxxxxxxxxxx} \",
\n \"AccessToken\": \"\"
\n}
When you make any queries, you can also pass a reference date as a parameter, using the date format yyyy-MM-dd (for example, 2019-06-05). This date is used as a reference for queries performed in the API or through back-tests, where it returns the data as it was on the date in question.
\nThe example below shows a GET and POST using a reference date at 'Addresses' dataset for people:
\nGet:
https://bigboost.bigdatacorp.com.br/peoplev2?
\nDatasets=addresses&
\nq=doc{xxxxxxxxxxx},referencedate{2018-09-03}&
\nAccessToken=
Post:
Body:
\n{
\n \"Datasets\": \"addresses\",
\n \"q\": \"doc{xxxxxxxxxxx},referencedate{2018-09-03}\",
\n \"AccessToken\": \"\"
\n}