Identity Data | Brazil | 155M Dataset | Verified National Profiles
1datapipe
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Verified Data Provider
Verified Data Provider|
national_id
|
id_type
|
address
|
address.latitude
|
address.longitude
|
lifestyle.location.dist
|
lifestyle.location.latitude
|
lifestyle.location.longitude
|
lifestyle.arts
|
lifestyle.arts.museum_and_theater_goers
|
lifestyle.arts.photo_and_video_enthusiasts
|
lifestyle.entertainment
|
lifestyle.entertainment.games_adventure
|
lifestyle.entertainment.games_arcade
|
lifestyle.entertainment.games_board
|
lifestyle.entertainment.games_card
|
lifestyle.entertainment.games_casino
|
lifestyle.entertainment.games_casual
|
lifestyle.entertainment.games_dice
|
lifestyle.entertainment.games_family
|
lifestyle.entertainment.games_music_and_rhythm
|
lifestyle.entertainment.games_puzzle
|
lifestyle.entertainment.games_racing_and_vehicle_simulators
|
lifestyle.entertainment.games_role_playing_games
|
lifestyle.entertainment.games_shooters_and_fps
|
lifestyle.entertainment.games_simulation
|
lifestyle.entertainment.games_sports
|
lifestyle.entertainment.games_strategy
|
lifestyle.entertainment.games_trivia
|
lifestyle.entertainment.games_word
|
lifestyle.food_and_drink
|
lifestyle.food_and_drink.foodies_or_cooking_enthusiasts
|
lifestyle.food_and_drink.restaurant_frequenters
|
lifestyle.health_and_fitness
|
lifestyle.health_and_fitness.fitness_enthusiasts
|
lifestyle.health_and_fitness.gym_goers
|
lifestyle.health_and_fitness.runners_or_joggers
|
lifestyle.interests_and_activities
|
lifestyle.interests_and_activities.country_club_members
|
lifestyle.interests_and_activities.gamers
|
lifestyle.interests_and_activities.movie_goers
|
lifestyle.interests_and_activities.news_readers
|
lifestyle.interests_and_activities.reading_enthusiasts
|
lifestyle.retail
|
lifestyle.retail.beauty_and_health_buyers
|
lifestyle.retail.big_box_retailer_shoppers
|
lifestyle.retail.cpg_buyers
|
lifestyle.retail.consumer_electronics_buyers
|
lifestyle.retail.department_store_value_shoppers
|
lifestyle.retail.fashion_shoppers_or_fashion_followers
|
lifestyle.retail.hotel_visitors
|
lifestyle.retail.sports_and_outdoor_buyers
|
lifestyle.retail.upscale_shoppers
|
lifestyle.retail.young_and_hip_shoppers
|
lifestyle.sports
|
lifestyle.sports.golf_enthusiasts
|
lifestyle.sports.soccer_enthusiasts
|
lifestyle.sports.sports_enthusiasts
|
lifestyle.telecommunication
|
lifestyle.telecommunication.downloaders
|
lifestyle.telecommunication.dual_sim_phone_users
|
lifestyle.travel
|
lifestyle.travel.air_travelers
|
lifestyle.travel.business_travelers
|
lifestyle.travel.leisure_travelers
|
lifestyle.life_stages
|
lifestyle.life_stages.singles
|
lifestyle.life_stages.college_students
|
lifestyle.general_demographics
|
lifestyle.general_demographics.55+
|
lifestyle.general_demographics.male
|
lifestyle.general_demographics.18-24
|
lifestyle.general_demographics.25-34
|
lifestyle.general_demographics.35-44
|
lifestyle.general_demographics.45-54
|
lifestyle.general_demographics.female
|
lifestyle.general_demographics.low_income
|
lifestyle.general_demographics.high_income
|
lifestyle.general_demographics.young_mothers
|
lifestyle.general_demographics.average_income
|
lifestyle.general_demographics.millennial_males
|
lifestyle.general_demographics.families_with_kids
|
lifestyle.general_demographics.millennial_females
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx |
| Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | Xxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxx | Xxxxxx | xxxxxxxxx | xxxxxxx |
| xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxx | xxxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxx |
| Xxxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | Xxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxx | xxxxxxxx | xxxxx | Xxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx |
| Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxx | Xxxxx | Xxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxx | Xxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxxx | xxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxx | xxxxx | xxxxx | Xxxxxxxxx | xxxxx | Xxxxx | Xxxxxx | xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxxx | xxxxxxxx |
| Xxxxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxxx | Xxxxx | xxxxx | xxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxx | xxxxxx | xxxxxx | Xxxxxx | xxxxxx | xxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxx | xxxxxx | xxxxx | xxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx |
| Xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxx | xxxxxx | Xxxxxxxx | Xxxxx | xxxxx | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxx | Xxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxx | xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxx | Xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxxxx | xxxxx |
| Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxx | xxxxx | xxxxxxx | xxxxxxxx | xxxxxx | xxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxx | xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxxxx | Xxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | xxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxx | xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxx | xxxxxxx | Xxxxxx | Xxxxxx | xxxxxxx | Xxxxxxx | Xxxxx | Xxxxxxxxxx |
| Xxxxxxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | Xxxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | Xxxxxx | xxxxxxxx | xxxxxx | xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxx | Xxxxxx | xxxxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxx | xxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | xxxxx | xxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxx | xxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxx | Xxxxxxx | xxxxx | Xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxx | xxxxxxx | xxxxx |
| Xxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxx | xxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxx | xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxxxx | xxxxxx | xxxxxxxxxx | xxxxx | xxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxxxxxx | Xxxxxxxxx | Xxxxxx | xxxxxxxx | xxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxx | xxxxxx | Xxxxx | xxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxx | xxxxxx | xxxxxx | xxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | xxxxx | Xxxxxx | Xxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxxx | Xxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxx | Xxxxxx | xxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx |
Volume
156M
RECORDS
Avail. Format
.csv
File
Coverage
1
Country
History
12
months
Data Dictionary
[Sample] Geo Sample 10 Br
| Attribute | Type | Example | Mapping |
|---|---|---|---|
|
national_id
|
Integer | 24777834015 | |
|
id_type
|
String | CPF | |
|
address
|
String | Recanto de Ribeiro, 12 Pastor, SP 21832-051 | |
|
address.latitude
|
Float | -47.810111 | |
|
address.longitude
|
Float | 131.60751 | |
|
lifestyle.location.dist
|
Float | 34.26 | |
|
lifestyle.location.latitude
|
Float | -47.81 | |
|
lifestyle.location.longitude
|
Float | 131.608 | |
|
lifestyle.arts
|
Float | 0.98 | |
|
lifestyle.arts.museum_and_theater_goers
|
Float | 0.03 | |
|
lifestyle.arts.photo_and_video_enthusiasts
|
Float | 0.14 | |
|
lifestyle.entertainment
|
Float | 0.41 | |
|
lifestyle.entertainment.games_adventure
|
Float | 0.37 | |
|
lifestyle.entertainment.games_arcade
|
Float | 0.97 | |
|
lifestyle.entertainment.games_board
|
Float | 0.49 | |
|
lifestyle.entertainment.games_card
|
Float | 0.4 | |
|
lifestyle.entertainment.games_casino
|
Float | 0.39 | |
|
lifestyle.entertainment.games_casual
|
Float | 0.92 | |
|
lifestyle.entertainment.games_dice
|
Float | 0.26 | |
|
lifestyle.entertainment.games_family
|
Float | 0.43 | |
|
lifestyle.entertainment.games_music_and_rhythm
|
Float | 0.86 | |
|
lifestyle.entertainment.games_puzzle
|
Float | 0.44 | |
|
lifestyle.entertainment.games_racing_and_vehicle_simulators
|
Float | 0.55 | |
|
lifestyle.entertainment.games_role_playing_games
|
Float | 0.82 | |
|
lifestyle.entertainment.games_shooters_and_fps
|
Float | 0.52 | |
|
lifestyle.entertainment.games_simulation
|
Float | 0.53 | |
|
lifestyle.entertainment.games_sports
|
Float | 0.28 | |
|
lifestyle.entertainment.games_strategy
|
Float | 0.27 | |
|
lifestyle.entertainment.games_trivia
|
Float | 0.95 | |
|
lifestyle.entertainment.games_word
|
Float | 0.5 | |
|
lifestyle.food_and_drink
|
Float | 0.02 | |
|
lifestyle.food_and_drink.foodies_or_cooking_enthusiasts
|
Float | 0.96 | |
|
lifestyle.food_and_drink.restaurant_frequenters
|
Float | 0.03 | |
|
lifestyle.health_and_fitness
|
Float | 0.71 | |
|
lifestyle.health_and_fitness.fitness_enthusiasts
|
Float | 0.64 | |
|
lifestyle.health_and_fitness.gym_goers
|
Float | 0.31 | |
|
lifestyle.health_and_fitness.runners_or_joggers
|
Float | 0.58 | |
|
lifestyle.interests_and_activities
|
Float | 0.56 | |
|
lifestyle.interests_and_activities.country_club_members
|
Float | 0.86 | |
|
lifestyle.interests_and_activities.gamers
|
Float | 0.78 | |
|
lifestyle.interests_and_activities.movie_goers
|
Float | 0.5 | |
|
lifestyle.interests_and_activities.news_readers
|
Float | 0.21 | |
|
lifestyle.interests_and_activities.reading_enthusiasts
|
Float | 0.63 | |
|
lifestyle.retail
|
Float | 0.13 | |
|
lifestyle.retail.beauty_and_health_buyers
|
Float | 0.5 | |
|
lifestyle.retail.big_box_retailer_shoppers
|
Float | 0.42 | |
|
lifestyle.retail.cpg_buyers
|
Float | 0.36 | |
|
lifestyle.retail.consumer_electronics_buyers
|
Float | 0.74 | |
|
lifestyle.retail.department_store_value_shoppers
|
Float | 0.31 | |
|
lifestyle.retail.fashion_shoppers_or_fashion_followers
|
Float | 0.27 | |
|
lifestyle.retail.hotel_visitors
|
Float | 0.62 | |
|
lifestyle.retail.sports_and_outdoor_buyers
|
Float | 0.2 | |
|
lifestyle.retail.upscale_shoppers
|
Float | 0.3 | |
|
lifestyle.retail.young_and_hip_shoppers
|
Float | 0.17 | |
|
lifestyle.sports
|
Float | 0.69 | |
|
lifestyle.sports.golf_enthusiasts
|
Float | 0.29 | |
|
lifestyle.sports.soccer_enthusiasts
|
Float | 0.81 | |
|
lifestyle.sports.sports_enthusiasts
|
Float | 0.08 | |
|
lifestyle.telecommunication
|
Float | 0.06 | |
|
lifestyle.telecommunication.downloaders
|
Float | 0.81 | |
|
lifestyle.telecommunication.dual_sim_phone_users
|
Float | 0.76 | |
|
lifestyle.travel
|
Float | 0.85 | |
|
lifestyle.travel.air_travelers
|
Float | 0.04 | |
|
lifestyle.travel.business_travelers
|
Float | 0.76 | |
|
lifestyle.travel.leisure_travelers
|
Float | 0.99 | |
|
lifestyle.life_stages
|
Float | 0.41 | |
|
lifestyle.life_stages.singles
|
Float | 0.17 | |
|
lifestyle.life_stages.college_students
|
Float | 0.38 | |
|
lifestyle.general_demographics
|
Float | 0.86 | |
|
lifestyle.general_demographics.55+
|
Float | 0.89 | |
|
lifestyle.general_demographics.male
|
Float | 0.81 | |
|
lifestyle.general_demographics.18-24
|
Float | 0.11 | |
|
lifestyle.general_demographics.25-34
|
Float | 0.27 | |
|
lifestyle.general_demographics.35-44
|
Float | 0.09 | |
|
lifestyle.general_demographics.45-54
|
Float | 0.54 | |
|
lifestyle.general_demographics.female
|
Float | 0.43 | |
|
lifestyle.general_demographics.low_income
|
Float | 0.77 | |
|
lifestyle.general_demographics.high_income
|
Float | 0.8 | |
|
lifestyle.general_demographics.young_mothers
|
Float | 0.93 | |
|
lifestyle.general_demographics.average_income
|
Float | 0.91 | |
|
lifestyle.general_demographics.millennial_males
|
Float | 0.25 | |
|
lifestyle.general_demographics.families_with_kids
|
Float | 0.63 | |
|
lifestyle.general_demographics.millennial_females
|
Float | 0.23 |
Description
LIVING IDENTITY INTELLIGENCE: The Gold Standard for Identity Intelligence in Emerging Markets
Privacy-first identity data across 18 high-growth markets. 1.35B+ real-world profiles powering fraud prevention, KYC/AML, digital onboarding, and AI-driven credit and risk modeling.
Living Identity™ is 1datapipe’s flagship dataset—an exclusive, high-integrity identity graph that provides 1.35B+ real-world verified profiles across 18 of the world’s most dynamic and data-scarce emerging markets. With 90–95% adult population coverage per country, it is the deepest identity dataset available outside traditional credit bureaus, and it is fully compliant, privacy-first, and legally licensed for enterprise use.
Each identity is tied to core national attributes—government-issued ID numbers, full names, addresses, phone numbers, emails, and date of birth—and cross-verified against telecom, financial, and commercial records. With continuous updates and strict normalization processes, Living Identity delivers AI-ready, structured data that powers decisioning where traditional data falls short.
This dataset helps organizations confidently verify, onboard, and model users across regions where fraud risk is high and legacy data is fragmented or unavailable. It offers a single source of truth for resolving identities at scale—unlocking new revenue, reducing regulatory exposure, and enabling inclusive growth.
DESIGNED FOR:
Banks, Fintechs & Credit Bureaus:
Enable real-time onboarding, digital KYC, thin-file scoring, and cross-border credit modeling with verified identity data in hard-to-penetrate markets.
Fraud & Identity Verification Platforms:
Detect synthetic identities, verify identity claims, and prevent account takeovers with population-scale data tied to official and telecom-based sources.
Risk & Compliance Teams:
Automate regulatory KYC/AML compliance across jurisdictions with datasets built to align with LGPD, PDPA, GDPR, and country-specific standards.
AI & Machine Learning Labs:
Train fraud, credit, and segmentation models using ground-truth data with verified input variables—improving performance, reducing bias, and boosting explainability.
Digital Ecosystems & Superapps:
Power seamless identity resolution for users across banking, e-commerce, remittances, and payments—enabling inclusive onboarding at scale in low-data environments.
OPTIMIZED FOR:
• Real-time digital onboarding with verified, high-coverage identity data
• KYC/AML automation aligned with LGPD, PDPA, GDPR, and regional frameworks
• Cross-border credit risk modeling and thin-file scoring in underserved markets
• Synthetic fraud detection and account takeover prevention using telecom-verified identity resolution
• AI training datasets for segmentation, risk scoring, and fraud analytics
• Inclusive identity verification for superapps, payments, and remittance ecosystems
Living Identity™ transforms identity from a barrier into an enabler—delivering trust, precision, and regulatory-grade intelligence to the organizations shaping the future of digital economies.
Country Coverage
South America
(1)
Brazil
History
12 months of historical data
Volume
| 156 million | RECORDS |
Pricing
1datapipe has not published pricing information for this product yet.
You can request detailed pricing information below.
Suitable Company Sizes
Small Business
Medium-sized Business
Enterprise
Delivery
Methods
SFTP
Frequency
monthly
Format
.csv
Use Cases
Market Research
Location-based Audience Analytics
Customer Intelligence
Marketing Intelligence
Know Your Customer (KYC)
Categories
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Frequently asked questions
What is Identity Data Brazil 155M Dataset Verified National Profiles?
LIVING IDENTITY INTELLIGENCE: The Gold Standard for Identity Intelligence in Emerging Markets Privacy-first identity data across 18 high-growth markets. 1.35B+ real-world profiles powering fraud prevention, KYC/AML, digital onboarding, and AI-driven credit and risk modeling.
What is Identity Data Brazil 155M Dataset Verified National Profiles used for?
This product has 5 key use cases. 1datapipe recommends using the data for Market Research, Location-based Audience Analytics, Customer Intelligence, Marketing Intelligence, and Know Your Customer (KYC). Global businesses and organizations buy Consumer Marketing Data from 1datapipe to fuel their analytics and enrichment.
Who can use Identity Data Brazil 155M Dataset Verified National Profiles?
This product is best suited if you’re a Enterprise looking for Consumer Marketing Data. Get in touch with 1datapipe to see what their data can do for your business and find out which integrations they provide.
How far back does the data in Identity Data Brazil 155M Dataset Verified National Profiles go?
This product has 12 months of historical coverage. It can be delivered on a monthly basis.
Which countries does Identity Data Brazil 155M Dataset Verified National Profiles cover?
This product includes data covering 1 country like Brazil. 1datapipe is headquartered in United States of America.
How much does Identity Data Brazil 155M Dataset Verified National Profiles cost?
Pricing information for Identity Data Brazil 155M Dataset Verified National Profiles is available by getting in contact with 1datapipe. Connect with 1datapipe to get a quote and arrange custom pricing models based on your data requirements.
How can I get Identity Data Brazil 155M Dataset Verified National Profiles?
Businesses can buy Consumer Marketing Data from 1datapipe and get the data via SFTP. Depending on your data requirements and subscription budget, 1datapipe can deliver this product in .csv format.
What is the data quality of Identity Data Brazil 155M Dataset Verified National Profiles?
You can compare and assess the data quality of 1datapipe using Datarade’s data marketplace.
What are similar products to Identity Data Brazil 155M Dataset Verified National Profiles?
This product has 3 related products. These alternatives include Consumer Marketing Data, Audience Targeting Data- B2C Consumer Audience Builder USA - Identity Graph Data, GeoPersona Brand Segments US Segmentation Data Available Globally GDPR-Compliant, and Consumer Behavior Data B2C Individual Consumer US 300 Million Records Identity Graph, Linkage, Modeling, AI, Propecting, Audience. You can compare the best Consumer Marketing Data providers and products via Datarade’s data marketplace and get the right data for your use case.
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