Case Studies

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Geodash

Bringing Location Intelligence Natively Into Enterprise BI

Geodash  case study hero image

3x

spatial engine times

8

real time rendering processes

100%

map data sources supported

The Challenge

Most geospatial tools require their own separate server environment and metadata layer, adding cost, complexity, and a second system for teams to maintain outside their existing BI platform. What was needed was a way to visualize existing BI data geographically, directly inside the BI environment itself, giving business users mapping, drill-down, and geographic analysis without leaving their existing workflow, without standing up new infrastructure, and without exposing sensitive enterprise data to third-party mapping services.

Our Execution

We engineered a native geospatial layer for the existing BI infrastructure, built to inherit the platform's drilling, pivoting, metadata, and security functions rather than duplicating them in a separate system. Heavy geospatial processing, geocoding, shape rendering, tile generation, runs in the cloud, while sensitive enterprise data never leaves the BI ecosystem. We integrated real-time geocoding, automatic pin clustering with drill-down to sub-clusters, heat-mapping by metric or quantity, and custom shape file generation, letting users define and reuse their own territories without backend involvement. The platform extends to mobile on iOS and Android, and supports data ingestion from multiple formats, KML, GeoJSON, ESRI shapefiles, and government-supplied spatial data, through both scheduled ETL and manual imports.

Discover What We Could Build

Let's talk about turning your existing BI data into something you can actually see on a map.