Platform Combines Visual Analytics, Vector Mapping
Geospatial analytics is scaling up for applications like the Internet of Things and climate analysis with the integration of the vector mapping technology and a visual analytics platform.
Arcadia Data said this week it has combined its visual analytics framework with MapGL vector mapping with the goal of providing “more granular visual geospatial analytics.” The integration brings together Mapbox GL’s GPU-based rendering engine with Arcadia Data’s recently announced GPU-accelerated visualization platform.
Mapbox GL is the library of custom online maps developed by Mapbox and used by Uber, Foursquare and others.
Arcadia Data, San Mateo, Calif., said Tuesday (Dec. 18) the combination would allow users to visualize geospatial shapes within various demographic parameters. The result would be more detailed location analytics owing to the platform’s ability to handle queries of billions of rows of data. Those data represent millions of geospatial shapes, the company added.
“Geospatial visualizations were previously limited by traditional technologies that could not scale to the data volumes and granularities that enterprises require today,” said Priyank Patel, Arcadia Data’s co-founder and chief product officer. “The new capability combines powerful mapping capabilities from Mapbox with our big data architecture to create an analytical environment free of the prior constraints of visualizing geospatial data.”
The maps and locations integration is touted as creating new business intelligence use cases, added Mapbox’s Matt Irwin, including “monitoring nationwide cellular networks at the building level in real time.”
Other emerging use cases range from tracking the spread of disease to vehicle and fleet management, the partners said.
Arcadia Data’s platform works with data lake technologies supporting fast-moving data, including Apache Kafka, Apache Solr and Apache Kudu. The platform is designed to allow users to view mapping data in real time.
The partners said the integration of Mapbox GL with the visual analytics platform helps overcome current limits on the number of geospatial shapes used, for example, to delineate geographical boundaries. The combination of data scaling and granular analytics is touted as allowing users to analyze query results from billions of records.
In addition, dynamic map rendering on live data moves beyond traditional static mapping techniques that rely on underlying IT resources to process data.
“The challenge doesn’t lie with the mapping technologies themselves, but rather, in the analytics platform that serves up the data,” Arcadian Data noted in a blog post. “Our integration with Mapbox GL lets [users] take advantage of big data stores and present geospatial visualizations without the limitations found in traditional [business intelligence tools that incorporate mapping.”