Alternative data datasets
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Granular U.S. population characteristics summarized at multiple territorial scales ranging from national to local.
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Three-dimensional mobility measurements capturing velocity, elevation, and positional accuracy to support advanced location-based analytics.
International points-of-interest dataset drawn from more than fifteen million consented venues across approximately one hundred fifty countries, offering privacy-respecting insights.
Location-based analytics derived from worldwide points of interest combined with pedestrian visit patterns.
Per-day visit counts across more than two thousand Home Depot stores, used as a proxy for residential construction and remodeling demand.
Datasets that support and feed geographic information system (GIS) applications.
The dataset offers durable location-based movement information collected through mobile applications and software development kits from partner organizations.
Geographic intelligence supporting over 18 million United States sites of interest for decision-making.
Geographic datasets that support GIS platform functionality.
Detailed human movement and location datasets.
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Geographic information covering points of interest with ties to categories and brands.
Visitor traffic figures by location or country that indicate footfall at specific points of interest.
Geographic and location-based information supplied to support GIS platforms and spatial analytics.
Daily measurements of customer visits, store traffic counts, and trade areas for individual locations of the biggest U.S. retail chain.
The dataset lists mobile device identifiers grouped by user behavior patterns and the physical locations they frequent.
Mobile Advertising IDs are categorized according to behavioral signals and venue visits tied to the automotive sector.
Mobile Advertising IDs are classified by behavioral attributes and location visits relevant to business and financial services.
Consumer mobile device IDs are organized around dining-related behaviors and the establishments those users visit.
The collection offers device identifiers categorized by lifestyle interests and the places users are observed visiting.
Device identifiers are sorted by shopping-related behaviors and the physical locations where those consumers shop.
Mobile device IDs are grouped based on travel interests and the destinations users are known to visit.
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The feed catalogs IP addresses flagged as fraudulent, including Tor exit nodes, VPN endpoints, and associated risk scores.
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