Indonesia Point of Interest (POI) Data

#	dataplor_id	parent_location	name	main_category	sub_category	sub_sub_category	business_category	naics_code	sic_code	chain_id	chain_name	parent_chain_path	chain_uuid_path	store_number	stock_ticker	phone	address	address2	h3_index	neighborhood	city	state	postal_code	country_code	country	latitude	longitude	dataplor_status	data_quality_confidence_score	open_closed_status	open_closed_status_confidence_score	opened_on	closed_on	website	monday_open	monday_close	tuesday_open	tuesday_close	wednesday_open	wednesday_close	thursday_open	thursday_close	friday_open	friday_close	saturday_open	saturday_close	sunday_open	sunday_close
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Volume

19M

Business Records

Avail. Formats

.json and .csv

File

Coverage

Country

History

years

[Sample] dataplor_Indonesia_Categories_Sample.csv

Attribute	Type	Example	Mapping
dataplor_id	String	016b9752-b75a-4b96-afa2-a1dfc28e01b5	POI ID
parent_location	String
name	String	Oorange - Pusat Inkubator Bisnis dan kewirausahaanUNPAD	POI Name
main_category	String	professional_services	POI Category
sub_category	String	licensed_professional	POI Sub-category
sub_sub_category	String		POI Sub-category
business_category	String	business_management_consultant	Product Category
naics_code	Float	541911	Company NAICS Code
sic_code	Float	0279	Company SIC Code
chain_id	String	12456789	Brand ID
chain_name	String	Coca Cola	Brand Name
parent_chain_path	String
chain_uuid_path	String
store_number	String
stock_ticker	String	AAPL	Stock Ticker
phone	String	############	POI Telephone
address	String	. * .##	Address
address2	String	# ****** , *****, #####, ***	Address
h3_index	String	8f8c16b6db20b52
neighborhood	String	Citarum, Bandung Wetan	Neighborhood Name
city	String	Bandung	City Name
state	String	Jawa Barat	State Name
postal_code	String	40115	Postal Code
country_code	String	id	Country Code Alpha-2
country	String	Indonesia	Country Name
latitude	Float	-6.90409557	Latitude
longitude	Float	107.6173912	Longitude
dataplor_status	String	active
data_quality_confidence_score	String	0.9328964463
open_closed_status	String	open
open_closed_status_confidence_score	Float	0.298
opened_on	String	2016-03-26T00:00:00+00:00
closed_on	String
website	String	https://pib.unpad.ac.id/	Website
monday_open	String	8:00	POI Opening Hours
monday_close	String	16:00	POI Opening Hours
tuesday_open	String	8:00	POI Opening Hours
tuesday_close	String	16:00	POI Opening Hours
wednesday_open	String	8:00	POI Opening Hours
wednesday_close	String	16:00	POI Opening Hours
thursday_open	String	8:00	POI Opening Hours
thursday_close	String	16:00	POI Opening Hours
friday_open	String	8:00	POI Opening Hours
friday_close	String	16:00	POI Opening Hours
saturday_open	String		POI Opening Hours
saturday_close	String		POI Opening Hours
sunday_open	String		POI Opening Hours
sunday_close	String		POI Opening Hours

Product Attributes

Attribute	Type	Example	Mapping
address	String	******** #	Address
address2	String	# ****** , *****, #####, ***	Address
business_category	String	car_dealer	Product Category
chain_id	String	ford	Company ID
chain_name	String	Ford	Company Name
city	String	Zell im Wiesental	City Name
closed_on	String
country	String	Germany	Country Name
county_code	String	de	Country Code Alpha-2
dataplor_id	String	e0e6be09-0f30-4f28-a92d-4822c1920f8c	POI ID
dataplor_status	String	active
data_quality_confidence_score	String	0.982
latitude	Float	47.71441	Latitude
longitude	Float	7.87391	Longitude
main_category	String	automotive_services	POI Category
naics_code	Float	441110	Company NAICS Code
name	String	Autohaus Maszurimm	POI Name
neighborhood	String	Nob Hill	Neighborhood Name
opened_on	String	2016-09-05
open_closed_status	String	open
open_closed_status_confidence_score	String	0.95
parent_location	String	c4811653-bf26-4fd2-85cf-0c89e28740a8	Placekey
phone	String	############	POI Telephone
postal_code	String	79669	Postal Code
sic_code	Float	5511	Company SIC Code
state	String	Baden-Württemberg	State Name
stock_ticker	String	NYSE:F	Stock Ticker
store_number	String		Location ID
sub_category	String	automobile	POI Sub-category
sub_sub_category	String	services	POI Sub-category

dataplor's Indonesia POI dataset covers 19M+ businesses & services across the country, making it the most comprehensive location and business intelligence dataset available for Indonesia. dataplor's datasets are particularly valued for refreshing weekly.

dataplor's unparalleled POI (Point of Interest) dataset is your key to navigating the dynamic market of Indonesia. Our data isn't just broad—it's hyper-local, granular, and tailored to empower businesses with actionable insights for success. Whether you're a local startup or a multinational expanding your footprint, our data empowers you with: -Untapped Opportunities: Identify prime locations for your next retail store, restaurant, or branch office in bustling cities like Jakarta, Surabaya, or Bandung, or emerging hubs like Medan and Makassar. -Market Intelligence: Understand consumer behaviors and preferences in diverse regions like Java, Bali, Sumatra, and Kalimantan for strategic decision-making. -Competitive Edge: Gain a deeper understanding of your competition's presence and performance across Indonesia's islands. -Resource Optimization: Streamline logistics, delivery routes, and supply chain management for maximum efficiency, considering the unique challenges of Indonesia's geography. -Data-Driven Innovation: Develop targeted marketing campaigns, personalized customer experiences, and innovative solutions tailored to Indonesia's diverse cultural and economic landscape. We understand that every industry has unique data needs. Our comprehensive POI data fuels growth and innovation across: -E-commerce and Retail: Optimize delivery networks, understand consumer hotspots in major cities and rural areas, and plan strategic expansions in high-growth regions. -Financial Services: Strategically place ATMs, branches, and microfinance initiatives for maximum reach and impact, targeting both urban centers and underserved rural communities. -Tourism and Hospitality: Enhance the visitor experience by mapping attractions, identifying hidden gems across the archipelago, and understanding tourist movements in popular destinations like Bali, Yogyakarta, and Lombok. With dataplor's POI data, you're not just getting information—you're gaining a strategic advantage in one of the world's most dynamic markets.

Asia (1)

Indonesia

20 years of historical data

19 million

Business Records

Free sample available

10% discount if you buy via Datarade

License	Starts at
One-off purchase	Not available
Monthly License	Not available
Yearly License	Available
Usage-based	Available

Request detailed pricing

Methods

Frequency

Format

Retail

Business Intelligence (BI)

Expansion Strategy Development

Local Economic Forecasting

Location Planning

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80% match rate

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What is Indonesia Point of Interest (POI) Data?

dataplor’s Indonesia POI dataset covers 19M+ businesses & services across the country, making it the most comprehensive location and business intelligence dataset available for Indonesia. dataplor’s datasets are particularly valued for refreshing weekly.

What is Indonesia Point of Interest (POI) Data used for?

This product has 5 key use cases. dataplor recommends using the data for Retail, Business Intelligence (BI), Expansion Strategy Development, Local Economic Forecasting, and Location Planning. Global businesses and organizations buy Point of Interest (POI) Data from dataplor to fuel their analytics and enrichment.

Who can use Indonesia Point of Interest (POI) Data?

This product is best suited if you’re a Medium-sized Business or Enterprise looking for Point of Interest (POI) Data. Get in touch with dataplor to see what their data can do for your business and find out which integrations they provide.

How far back does the data in Indonesia Point of Interest (POI) Data go?

This product has 20 years of historical coverage. It can be delivered on a weekly, monthly, real-time, and on-demand basis.

Which countries does Indonesia Point of Interest (POI) Data cover?

This product includes data covering 1 country like Indonesia. dataplor is headquartered in United States of America.

How much does Indonesia Point of Interest (POI) Data cost?

Pricing information for Indonesia Point of Interest (POI) Data is available by getting in contact with dataplor. Connect with dataplor to get a quote and arrange custom pricing models based on your data requirements.

How can I get Indonesia Point of Interest (POI) Data?

Businesses can buy Point of Interest (POI) Data from dataplor and get the data via S3 Bucket. Depending on your data requirements and subscription budget, dataplor can deliver this product in .json and .csv format.

What is the data quality of Indonesia Point of Interest (POI) Data?

You can compare and assess the data quality of dataplor using Datarade’s data marketplace. dataplor has received 3 reviews from clients.

What are similar products to Indonesia Point of Interest (POI) Data?

This product has 3 related products. These alternatives include Germany Point of Interest (POI) Data, Shopper Data Malls & Shopping Centers in US Point-of-Interest (POI) Analysis, and SafeGraph Commercial Real Estate Data Global Real Estate Coverage 56M+ Places. You can compare the best Point of Interest (POI) Data providers and products via Datarade’s data marketplace and get the right data for your use case.

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One-off purchase	Not available
Monthly License	Not available
Yearly License	Available
Usage-based	Available

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Indonesia Point of Interest (POI) Data

Data Dictionary

Description

Country Coverage

History

Volume

Pricing

Suitable Company Sizes

Delivery

Use Cases

Categories

Related Searches

Related Products

Frequently asked questions

dataplor
Globally scaled, dynamically updated, and human-reviewed location intelligence.

Trusted by

Indonesia Point of Interest (POI) Data

Data Dictionary

Description

Country Coverage

History

Volume

Pricing

Suitable Company Sizes

Delivery

Use Cases

Categories

Related Searches

Related Products

Frequently asked questions

dataplor Globally scaled, dynamically updated, and human-reviewed location intelligence.

Trusted by

dataplor
Globally scaled, dynamically updated, and human-reviewed location intelligence.