Let me begin with a hypothetical scenario - well almost hypothetical but close to practical reality.
In case of real-estate/land business - We are aware of how insurance companies define their policies, ensuring adequate risks are evaluated and understood the circumstances, geographical/locational aspects where the real-estate is being brought. Is the piece of land in consideration an earthquake, flood, hurricane, landslides zone or any other natural hazard zone. Now to assess the risk of writing such a policy, the organization need to have the following:
1. Access to the different applications that capture the geospatial data e.g. weather monitoring and stats, maps, geographical patterns and history in the area etc.
2. Ways to extract and analyze the information from those applications
There lies in the opportunity to have such geospatial data extracted into a data model, transformed into the data warehouse and allow quick analysis for taking decisions around the specific geographical zone.
How is this going to help the organization - well, it will
1. reduce insurance companies overall risk exposure, with the analysis done before defining the policy
2. allow for effective decision capability while addressing such specialized needs
3. increase their bottom line and overall market revenue potential
Location Intelligence Defined - The geospatial data captures the precise coordinates of any location using Latitude and Longitude data. We have seen geospatial data in usage in our cell phones, GPS systems, Google Earth etc. The concept of location intelligence is to provide location sensitive context using geospatial data in the business decisions being made. This can be applicable to any industry, be it retail wherin a global grocery chain want to promote products based on the geographical patterns of the stores/regions or any other verticals.
Will bring more insights on how the data is structured and can be integrated with the existing BI infrastructure in coming blogs.