Global Places Dataset
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下载链接:
https://marketplace.databricks.com/details/7d8a9de6-96f6-475b-baba-1f66a30ce3a1/Foursquare_Global-Places-Dataset
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资源简介:
Foursquare has developed a map of the world using first-party data derived from over 14 billion explicit check-ins from our consumer apps and other high quality location data sources.
Foursquare’s Global Places dataset comes with 25 core attributes and a multitude of optional extended attributes (6 add-on options). The full data schema can be viewed [here](https://location.foursquare.com/places/docs/flat-file-data-schema).
For more information please speak to your Foursquare representative via databricks@foursquare.com.
Core Attributes Included:
- fsq_id
- name
- name_translated
- latitude/longitude
- geocodes
- address
- address_extended
- locality
- dma
- region
- postcode
- country
- admin_region
- post_town
- neighborhood
- po_box
- date_created
- date_refreshed
- fsq_category_ids
- fsq_category_labels
- fsq_chain_id
- fsq_chain_name
- parent_id
- subvenue_count
- census_block_id
- closed_bucket
Rich Attribute Add On Options:
All Extended Attributes (91 fields)
- Ratings, Hours, & Social Media (13 fields)
- Tips and Tastes (3 fields)
- Best Photos (2 fields)
- Calculated Scores (4 fields)
- Tags (68 fields)
- Data Matching (1 field)
**
Use Case Examples:**
- Place Search/Recommendation for Consumer Experience. Types of customers range from social platforms (e.g. enabling global geotags for Twitter) to food delivery services (e.g. restaurant discovery for sales outreach) to ride hail (e.g. address and place name matching for Uber).
- Trade area analysis, competitive analysis, and market research. Businesses with a physical footprint will benefit from Foursquare Places data to better enable site selection decisions and unlock the potential value of a geolocation.
- Transaction data enrichment. Transaction data can be messy, inconsistent, and lack key information necessary to give context to the transaction. By joining transaction data with POI data, businesses can better understand buyer behavior and model spend patterns – this enriched data helps improve products and delivers more engaging customer experiences
For more information please reach out to databricks@foursquare.com
提供机构:
Foursquare



