Alternative data datasets
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This is a Techsalerator dataset on Foot Traffic & Mobility Data for Nicaragua
Analyzing the Impact of the Pandemic on Low-Income Populations
Mobility scores describing movement around venues and neighbourhoods, used in real-estate and retail analysis and including migration flows and travel-distance statistics.
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Foot-traffic panels built from mobile-device location signals, measuring visits, dwell time and cross-shopping for US retailers, malls and real-estate assets, delivered on a daily schedule to investors and real-estate desks.
Indexes built from foot-traffic location data for Japanese business sites including production facilities and retail outlets.
Foot-traffic-based indices covering locations operated by Japanese real estate investment trust firms.
Location-driven metrics derived from foot-traffic patterns at Japanese real estate investment trust properties.
Location-based indices calculated from foot-traffic signals for Japanese corporate sites such as plants and stores.
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On-the-ground audits of retail shelves: store-level inventory and condition snapshots collected by contracted field visitors with geolocation context: a direct check on availability and product presence.
American points-of-interest records grouped into 14 sectors and 120 sub-industry classifications.
Adentro Foot Traffic dataset contains daily breakdown of consumer foot traffic at the census block group, zip, city and state across the US. Adentro Foot Traffic dataset is privacy-compliant and uniquely sourced via direct access to 50M+ US consumers in the Adentro Network, and is built with Adentro powered guest wifi software that is trusted and deployed by leading retail enterprises and brick &
ShopAnalytics is an AI-powered solution that connects to existing surveillance cameras to analyze customer behavior in real time. It provides retailers with actionable insights on traffic patterns, dwell time, and customer engagement, helping optimize store layout, improve sales performance, and enhance the shopping experience.
UST Wi-Fi Analytics with Retail Analytics and Shopper Insights is a cloud-native in-store analytics platform built on AWS that turns your existing Wi-Fi network into a rich source of retail analytics. By passively detecting Wi-Fi enabled devices, it delivers privacy-conscious footfall, dwell time, zone traffic, and path analysis across every store, without beacons or new hardware. Retailers use Wi
An end-to-end, customized solution to democratize quick and fast access to valuable data across various data sources, such as emails, documents, invoices, delivery notes, company knowledge-base sources (e.g. Confluence, Sharepoint and many others.), but also complex unstructured documents, such as drawings, hand-written notes, etc. Crayon’s AWS Gen AI Professional Services equips businesses with k
Shopper movement and visitation drawn from mobile location signals around the world, used to size footfall, attribute out-of-home campaigns and choose store sites.
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Estimated retail foot traffic built from anonymized mobile device location observations.
A compilation of menu offerings, their ingredients, and flavor profiles drawn from a representative selection of sources.
A reference set of notable sites connected to particular travel destinations.
OpenStreetMap node features for Australia, supplemented with additional attributes that support category-based filtering.
OpenStreetMap node features for Canada, supplemented with additional attributes that support category-based filtering.
OpenStreetMap node features for Mexico, supplemented with additional attributes that support category-based filtering.
OpenStreetMap node features for Spain, supplemented with additional attributes that support category-based filtering.
OpenStreetMap node features for the United Kingdom, supplemented with additional attributes that support category-based filtering.
Collection of datasets under the places theme that provide point-based geographic markers for various facilities, services, businesses, and amenities.
Demographic breakdowns by age and sex, counts of points of interest, and supplementary attributes designed for geospatial analytics.
Population statistics segmented by age and gender, POI tallies, and additional variables aimed at spatial analysis.
Inhabitants counts along with age and gender distributions, location-based landmark tallies, and other inputs suited for geographic modeling.
Sample point-of-interest records with geographic coordinates, mailing addresses, associated stock symbols, and additional fields for every Dutch Bros Coffee outlet.
A points-of-interest sample featuring coordinates, mailing addresses, stock symbols, and other fields for every U.S. Walmart store.
Normalized United States retail foot-traffic figures broken down by state in 15-minute intervals.
A dataset enabling audience construction by identifying consumers who have previously been to designated places or establishments.
Subnational and regional statistical series maintained across European Union member territories.
Statistical collections on commercial activity, corporate operations, and tourism across the European Union.
Location-based intelligence covering points of interest and pedestrian movement patterns.
Get a data sample: Large scale foot traffic data and audience data across web and telecom, enriched with 30+ attributes and updated frequently to power foot traffic targeting and attribution.
Get a data sample: Malaysian and Singaporean cross-border geospatial data providing geospatial insights into commuter and leisure traveler patterns, refreshed to power geospatial audience targeting and CRM enrichment for retail brands, financial institutions, and telecommunication companies in both
Get a data sample: Geospatial data for travel segments providing geospatial insights into audience travel patterns and mobility, refreshed frequently to power targeted advertising, CRM enrichment, and geospatial insights.
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airline-disruption-data is a tabular dataset of U.S. domestic flight records published on the datasets hub, tagged as covering between 10 million and 100 million rows in Parquet format. The schema describes per-flight scheduling, delay, cancellation, and routing fields.
The airline-disruption-data-phase1b dataset is a tabular release hosted by publisher Dev123Hug456Face that compiles scheduled and actual flight-level operations data with delay, cancellation and diversion flags. It is distributed as a single Parquet split of roughly 12 million rows.
Labor-market metrics on talent availability, hiring needs, compensation, competencies, demographic representation, workforce mobility, and recruitment patterns segmented by occupation and location.
Corporate-action reference date indicating when securities are distributed, supporting prompt and practical allocation information.
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