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It becomes harder to find meaningful relationships and key insights as the amount of data increases. Traditional GIS data management solutions, such as spatially-enabled relational database tables and file geodatabases, organize data using two-dimensional data structures with rows and columns. Relational databases are not well suited to traverse multiple levels of relationships across a large number of data points. Rather, they are optimized to join data across tables up to a few levels deep before running into performance problems.
As data sets increase in size, simply putting dots on a map can overwhelm users with too much irrelevant information. It becomes difficult, if not impossible, to sort through the noise to find the key insight they need.
A GeoPrism KG can build a web of meaningful relationships that connect trillions of points from several data sets to enable important discoveries. Once the data are in the graph, meaningful insights can be discovered that would be difficult or impossible to discover using traditional databases. The graph uses semantic relationships to convey concepts, categories of things, and how data are related to each other to automatically connect the dots for you, filter out the noise, and show you what you are looking for.