Visualize large datasets and own the experience
By: Ryan Baumann
With the new Mapbox GL heatmaps you can add powerful map data visualizations to your applications with minimal code. Integrating our maps natively, keeps your customer data private and allows you to control the entire experience for users.
You can customize every aspect of the data visualization and see trends in any data property, even when working with large datasets. Our heatmaps can also integrate with other developer tools, so you can maintain your workflow without relying on third party solutions.
Create fast maps with millions of points
Create heatmaps from massive telemetry, web traffic, and social media data. Real-time adjustments to color transitions, filters, and other style properties are performant at scale. Try it yourself with this map of automobile telemetry data across London.
See trends in any data property
With our heatmaps you can do spatial data aggregations to quickly understand average, minimum, and maximum trends, like this example of home insurance values and property aggregation. Users can interpret data at the state level down to individual homes. Explore the full map.
Stay within your workflow
Data scientists face many of the same challenges as BI developers, often exporting data into a third-party data viz tool. Using Mapbox, stay within your own data science workflow, like integrating our heatmaps with Jupyter notebooks:
Have questions? Reach out to sales about building heatmaps into your BI platform or dashboard. Get moving quickly with our GL JS heatmaps tutorial.
Heatmaps at scale for Business Intelligence was originally published in Points of interest on Medium, where people are continuing the conversation by highlighting and responding to this story.