What Is Geospatial Data and How Can It Save Your Life?

The number of extreme weather events, like hurricanes and blizzards, has been rising exponentially since 1980. The cost of these storms is also extreme. In North America alone, thunderstorm losses have doubled — from under US$10 billion in 1980 to almost $20 billion in 2015.

But analyzing geospatial data — any information with a geographical component such as GPS data, satellite imagery, city infrastructure maps, or weather data — can help mitigate the economic and human cost of natural disasters. SAP has taken steps recently to make it easier for customers to use location and enterprise data together.

Using the in-memory database and application platform SAP HANA, SAP has developed a prototype that helps organizations analyze geospatial data and predict how storms can impact a given region.

After years of collaboration with Esri, a leader in geographical information systems, the two companies announced tighter integration between SAP HANA and Esri’s “geodatabase” in January. This allows customers to analyze geographic information within their business processes and take action more easily. Previously, customers had to analyze location data separately from business applications, then combine them.

As Hasso Plattner, co-founder of SAP and chairman of the Supervisory Board of SAP SE, pointed out at SAPPHIRE NOW, SAP just took spatial capabilities one step further and released them as services that can pull weather or satellite data directly from providers into the enterprise data layer. Customers can now create location-aware application more quickly using this functionality, part of the recently-announced SAP HANA Data Management Suite.

Using these advancements, SAP created a software prototype that helps optimize risk management and mitigate the effects of natural disasters like hurricanes in Japan. The application brings together real-time weather data tracking storms’ progress, information about storm after-effects from the European Space Agency, and infrastructure maps, such as building and roads. Machine learning is used to help create a neural network that allows municipalities to identify vulnerable areas, predict the potential impact on crop yields, or anticipate wildfire hazards.

The prototype calculates a risk prediction based on four indexes — soil, water, steepness, and vegetation — so regional governments can prepare to react quickly in those areas. For example, if signs indicate a landslide risk, public officials can close roads or issue evacuation warnings earlier and save lives.

But this is only one example of how location data can be used by organizations. SAP is also working with a major amusement park to bring geographic information and customer sentiment into their marketing applications to help keep people in their park. For example, if someone tweets that they are sick of long waits for rides, marketing managers can respond in real time to send that person a fast pass for nearby rides that customers might enjoy based on their ride history.

“If you think about every business transaction, it’s about who and when it was created. But now if you can see where it was created, this opens up a new world of possibilities,” says Geoff Trembley, who heads up SAP HANA and Database Platform Market Strategy at SAP.