Geo analytics (or geospatial analytics) is the analysis of data that includes a geographic or spatial component. It helps organizations understand where things happen, not just what happens. Location often adds critical context to business decisions.

Examples of geo analytics include:

• Sales by region or territory

• Customer distribution by city

• Delivery route optimization

• Store performance by location

• Service outage mapping

Geo analytics uses spatial data such as latitude and longitude, addresses, postal codes, regions, or polygons. This data is visualized using maps, heatmaps, and spatial layers.

From a BI perspective, geo analytics enhances dashboards by adding spatial dimensions. Decision-makers can quickly identify geographic patterns, regional disparities, and location-based trends.

Technically, geo analytics relies on:

• Geocoding (converting addresses to coordinates)

• Spatial indexing

• Geospatial data types

• Map tile services

Modern BI tools integrate mapping capabilities directly into dashboards, allowing users to zoom, filter, and interact with geographic data.

Challenges include data accuracy, coordinate consistency, and privacy concerns when handling location data.

Geo analytics is widely used in retail, logistics, marketing, real estate, and public services, where location is a critical driver of performance.