Correlation of business entities in multiple data sources and delivering the consolidated results to master data management systems.
Ontology 4 automates the process of taking multiple incoming data sources, correlating the business entities present in the data before delivering the consolidated master data to MDM solutions. Its use of graph-based, semantic search technology provides a radically different approach to solving traditional data integration challenges that dramatically increases the quality of data in the MDM repository whilst reducing timescales and cost.
Ontology's semantic inference allows it to identify the same entity in different data sources where no correlation, such as a relational key, exists to link the entities. Ontology uses its understanding of the relationships and dependencies between the entities to infer that they are the same. In environments with complex data integration requirements, this ability results in a far higher degree of entity matching than traditional relational linking can achieve and makes more MDM projects viable.
Ontology's inherently agile technology allows data correlation initiatives to be managed by Agile or incremental methodologies. Solutions are delivered using the Ontology Data Integration Process, via a series of 2 week Discover, Design, Develop, Test "sprints", which means that changes in requirements such as the adding of additional data sources, or the changing of output formats that can delay or derail traditional Data Integration projects, can be easily captured and accommodated at any time. This approach ensures that requirements are fully met, de-risks projects and reduces timescales and costs.
Read how Ontology is rethinking data acquisition, data correlation and data migration projects for a post-Google world in our Agile Data Integration white paper.