Article
How geospatial data analytics provide strategic insight for organizations
Nov. 8, 2021
Geospatial data analytics, location analytics, or spatial business intelligence (BI) are interchangeable terms that relate to enriching data with a spatial or location component. The data your company retains about employees, facilities, customers, and transactions generally have a physical space associated with them.
Enhancing data with spatial components allows governments and companies to gain deep insights that add the “where” element to data about their citizens, clients, opportunities, project successes, and business growth.
What is geospatial data?
Geospatial data combines location, such as a region, street, or census block with information in a database. Examples can include purchasing habits by zip code combined with census block data such as age, average household income, race or ethnicity, educational attainment, or traffic patterns.
Data can be either static or real-time. The internet of things (IoT), including location sensors, mobile devices, and social media, provides additional information.
Examples of geospatial data
The potential in geospatial data comes from understanding the range of relevant information that an organization can gather and use to help make decisions.
Demographics
Demographic and social data includes indicators such as age, race, household income, educational attainment, and more.
Businesses and governments can use this information to determine where to locate new facilities and store fronts or to focus marketing efforts. Educational attainment, meanwhile, can be an indicator of availability for desired employee characteristics in a local labor pool. Companies can use household income data to help determine the location of facilities so they exist in a neighborhood with residents likely to use their services.
Environment
Environmental data is vast and various.
