Local Economic Development agencies are tasked with attracting new businesses to relocate to their areas. They typically do this by citing the various demographic, cost-of-living, educational, recreational and geographic advantages of their state, county, or metropolitan area. The goal is to present the data that makes their area look more attractive than another city or town.
The good news is most development agencies are sitting on a mountain of data. The bad news is most development agencies are sitting on a mountain of data.
That’s where TerraFrame can help.
The challenge really isn’t too much data. It’s that most data sets prepared by various private and public organizations are in a multitude of incompatible file formats or lack geocoding, which makes them ‘unmappable,’ vastly diminishing their use for geospatial analysis.
TerraFrame was hired by a development board to build an automated solution on top of our GeoPrism platform they could use themselves. We first acquired available data sets on economic and other statistics for the area as well as many others. Some were in GIS formats, but others were in standard spreadsheets.
We ‘geoprepped’ the raw data sets so they could be compared against each other and at any level of granularity the board wants. On the front end, we created a dynamic dashboard where the client can constantly re-aggregate the raw data, change the query parameters and view the results.
The result is an automated app the Economic Development agency can now use to import new raw data sets as they find them to create custom comparisons of their city against nearly any other in city in the United States. These comparisons may relate to economics, labor forces, housing prices, land costs and an infinite number of other categories.
With an automated data management app from TerraFrame, Economic Development agencies become more effective:
Analyze raw data in formats that were previously incompatible
Input nearly any demographic or economic data into their analyses
Quickly compare their area to any other in the nation
Change data aggregation and query parameters on the fly