Foursquare Launches Next-Generation Tiling System, Enabling Large-scale Geospatial Data Analytics Within Minutes

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Hex Tiles addresses the industry-wide challenge of unifying and visualizing big data to help companies quickly and easily analyze location data for better decision-making.

Location data and technology leader, Foursquare, unveiled Hex Tiles, the next-generation tiling system that revolutionizes the speed and efficiency of data analytics for businesses looking to perform large-scale geospatial analytics for decision-making purposes.

Developed by Unfolded, which Foursquare acquired in 2021, the system empowers data scientists to easily unify diverse spatial datasets, quickly visualize and explore big data on a planetary scale, and conduct on-the-fly analytics. This work can be done in a matter of minutes versus days.

“We developed Hex Tiles to tackle the challenges data scientists face in dealing with geospatial data.” Sina Kashuk, SVP of Unfolded at Foursquare, said. “With Hex Tiles, data scientists can easily bring their data together, enrich it with third party datasets, perform exploratory analyses and quickly share their results. Also, because it is able to encode the time dimension, the system addresses the complexities of working with spatiotemporal data.”

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“With Hex Tiles, data scientists can easily bring their data together, enrich it with third party datasets, perform exploratory analyses and quickly share their results. Also, because it is able to encode the time dimension, the system addresses the complexities of working with spatiotemporal data.”

Unification is a major challenge for data scientists attempting to work with geospatial data sets. Spatial data, in particular, comes in many different shapes, forms, types and sizes making it a difficult and time-consuming process to join data for visualization, exploration and analysis. With Hex Tiles, one can quickly and easily ingest diverse spatial datasets and transform them all into Hex Tiles. This not only simplifies the process of data unification and allows users to perform more efficient analytics, but provides greater opportunities for data enrichment. Users can combine diverse datasets from demographic information, to environmental readings, to POI, to movement data to achieve greater insight.

Unlike current tiling systems such as raster and vector tiles, Hex Tiles is an analytics tiling system that enables users to prepare and work with large, disparate datasets in a single platform without the need for coding. Hex Tiles also features a one-of-a-kind spatiotemporal analytics tile format that is more efficient than vector tiles for encoding data and is optimized for client-side analytics, unlike raster tiles. Hex Tile stores and uses data in tabular form, commonly used for analytics and machine learning.

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Developed using H3 – an open-source, hierarchical, discrete global grid system that breaks up the world into hexagonal cells – Hex Tiles allows users to easily work with any area of interest in a map without concerns about data size. Capable of processing hundreds of millions of rows of data in parallel, the system allows users to instantly and seamlessly analyze and explore massive datasets, all within their own browser through the Unfolded Platform.

“This is an exciting new technology milestone for us at Foursquare and the beginning of substantial investments we are making to drive innovation in the geospatial analytics and visualization space. Hex Tiles is a game-changer for data scientists and companies who need to conduct large-scale data analyses for site selection, competitive research and planning, and other forms of business intelligence,” said Gary Little, CEO of Foursquare. “The potential use cases for this technology are boundless.”

Hex Tiles are available now for clients and partners exclusively through Foursquare’s Unfolded Platform for geospatial data unification, enrichment, visualization and analytics. Unfolded’s integrated system allows Foursquare’s clients to access, merge, and analyze spatial data in almost any environment.

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