Demographic Data | Southeast Asia | 401M Records of Identity & Lifestyle | Multi-Country Package
Verified Data Provider|
national_id
|
id_type
|
names_1.name
|
names_1.last_seen
|
names_2.name
|
names_2.last_seen
|
names_3.name
|
names_3.last_seen
|
gender
|
dob
|
addresses_1.address
|
addresses_1.postcode
|
addresses_1.last_seen
|
addresses_2.address
|
addresses_2.postcode
|
addresses_2.last_seen
|
addresses_3.address
|
addresses_3.postcode
|
addresses_3.last_seen
|
phones_1.phone
|
phones_1.type
|
phones_1.last_seen
|
phones_2.phone
|
phones_2.type
|
phones_2.last_seen
|
phones_3.phone
|
phones_3.type
|
phones_3.last_seen
|
emails_1.name
|
emails_1.last_seen
|
emails_2.name
|
emails_2.last_seen
|
emails_3.name
|
emails_3.last_seen
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 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 |
Data Dictionary
| Attribute | Type | Example | Mapping |
|---|---|---|---|
|
national_id
|
Integer | 8009094425214905 | |
|
id_type
|
String | NIK | |
|
names_1.name
|
String | Calista A. | |
|
names_1.last_seen
|
DateTime | 2024-12-15T00:00:00+00:00 | |
|
names_2.name
|
String | Calista Ardianto | |
|
names_2.last_seen
|
DateTime | 2024-11-15T00:00:00+00:00 | |
|
names_3.name
|
String | Cal. Ardianto | |
|
names_3.last_seen
|
DateTime | 2024-01-15T00:00:00+00:00 | |
|
gender
|
Boolean | ||
|
dob
|
DateTime | 1950-01-08T00:00:00+00:00 | |
|
addresses_1.address
|
String | Gg. Jamika No. 832 Malang, JK 82470 | |
|
addresses_1.postcode
|
Integer | 82470 | |
|
addresses_1.last_seen
|
DateTime | 2024-06-15T00:00:00+00:00 | |
|
addresses_2.address
|
String | Jalan Jend. Sudirman No. 24 Pangkalpinang, JK 96575 | |
|
addresses_2.postcode
|
Integer | 96575 | |
|
addresses_2.last_seen
|
DateTime | 2024-04-15T00:00:00+00:00 | |
|
addresses_3.address
|
String | Gang Jakarta No. 210 Surakarta, JK 53000 | |
|
addresses_3.postcode
|
Integer | 53000 | |
|
addresses_3.last_seen
|
DateTime | 2024-01-15T00:00:00+00:00 | |
|
phones_1.phone
|
Float | 7079278744.0 | |
|
phones_1.type
|
String | HOME | |
|
phones_1.last_seen
|
DateTime | 2024-12-15T00:00:00+00:00 | |
|
phones_2.phone
|
Integer | 620266181764 | |
|
phones_2.type
|
String | HOME | |
|
phones_2.last_seen
|
DateTime | 2024-11-15T00:00:00+00:00 | |
|
phones_3.phone
|
Integer | 625129425711 | |
|
phones_3.type
|
String | HOME | |
|
phones_3.last_seen
|
DateTime | 2024-01-15T00:00:00+00:00 | |
|
emails_1.name
|
String | skywalker866@email.com | |
|
emails_1.last_seen
|
DateTime | 2024-11-15T00:00:00+00:00 | |
|
emails_2.name
|
String | calista0108@email.com | |
|
emails_2.last_seen
|
DateTime | 2024-09-15T00:00:00+00:00 | |
|
emails_3.name
|
String | calista1950@email.com | |
|
emails_3.last_seen
|
DateTime | 2024-01-15T00:00:00+00:00 |
Description
Country Coverage
History
Volume
| 401 million | Records |
Pricing
Suitable Company Sizes
Quality
Delivery
Use Cases
Categories
Related Searches
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Frequently asked questions
What is Demographic Data Southeast Asia 401M Records of Identity & Lifestyle Multi-Country Package?
GEOLIFESTYLE INTELLIGENCE: Uncover Lifestyle Patterns with Geospatial Precision Our demographic datasets include rich geo-spatial attributes that power hyper-local segmentation, regional risk scoring, and location-driven behavioral insights — essential for growth in financial services.
What is Demographic Data Southeast Asia 401M Records of Identity & Lifestyle Multi-Country Package used for?
This product has 5 key use cases. 1datapipe recommends using the data for Location-based Audience Analytics, Consumer Intelligence, Marketing Intelligence, Know Your Customer (KYC), and Marketing Strategy. Global businesses and organizations buy Demographic Data from 1datapipe to fuel their analytics and enrichment.
Who can use Demographic Data Southeast Asia 401M Records of Identity & Lifestyle Multi-Country Package?
This product is best suited if you’re a Enterprise looking for Demographic 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 Demographic Data Southeast Asia 401M Records of Identity & Lifestyle Multi-Country Package go?
This product has 6 months of historical coverage. It can be delivered on a monthly basis.
Which countries does Demographic Data Southeast Asia 401M Records of Identity & Lifestyle Multi-Country Package cover?
This product includes data covering 5 countries like Indonesia, Thailand, Malaysia, Philippines, and Vietnam. 1datapipe is headquartered in United States of America.
How much does Demographic Data Southeast Asia 401M Records of Identity & Lifestyle Multi-Country Package cost?
Pricing information for Demographic Data Southeast Asia 401M Records of Identity & Lifestyle Multi-Country Package 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 Demographic Data Southeast Asia 401M Records of Identity & Lifestyle Multi-Country Package?
Businesses can buy Demographic 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 Demographic Data Southeast Asia 401M Records of Identity & Lifestyle Multi-Country Package?
1datapipe has reported that this product has the following quality and accuracy assurances: 95% ID Number, 93% Gender, 87% Address. You can compare and assess the data quality of 1datapipe using Datarade’s data marketplace.
What are similar products to Demographic Data Southeast Asia 401M Records of Identity & Lifestyle Multi-Country Package?
This product has 3 related products. These alternatives include Identity & Lifestyle Data LATAM 243M Dataset Marketing & Consumer Intelligence Key Markets Insights, Doorda UK Population Data Geodemographic Data Linked to 2.2M+ Postcodes from 173 Data Sources Location Intelligence and Analytics, and Crime Risk Insurance Data USA & Canada Make Informed Insurance Underwriting Decisions Location Data Demographic Data. You can compare the best Demographic Data providers and products via Datarade’s data marketplace and get the right data for your use case.
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