Data Integration
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Meaningful insights are discovered by bringing together data from multiple different sources. But there is a problem. Data from different sources do not fit together easily due to incompatible data formats, schemas, and vocabularies. The same spatial data can be represented in multiple different ways including GPS coordinates, geometries, addresses, identifiers, and text labels. Labor intensive “data cleaning” efforts are needed to normalize disparate data for business intelligence reporting and stakeholder decision support.
Meaningful insights are discovered by bringing together data from multiple different sources. But there is a problem. Data from different sources do not fit together easily due to incompatible data formats, schemas, and vocabularies. The same spatial data can be represented in multiple different ways including GPS coordinates, geometries, addresses, identifiers, and text labels. Labor intensive “data cleaning” efforts are needed to normalize disparate data for business intelligence reporting and stakeholder decision support.
GeoPrism
GeoPrism utilizes next generation data blending, data indexing, and data transformation technology for intelligent data driven systems.
Integrate
GeoPrism uses semantic technologies to reconcile disparate data schemas, terms, and spatial data formats using an ontology-driven learning engine to get data from different silos to align and integrate with each other. These algorithms have been developed over a number of years in response to customer-driven data integration challenges.
Index
Intelligent data indexes across silos can be built using a metadata repository that allows you to search for data across the enterprise.
Transform
GeoPrism KG can transform and aggregate both spatial and non-spatial data on demand to create more meaningful views of your data in the format required by your business intelligence and ML tools.