Conventional data management capabilities are ill-equipped to handle the increasingly challenging data demands given the volume and speed at which data is created. And that is only going to get more challenging. This interesting topic came to our attention from Database Trends and Applications in their article, “Knowledge Graphs and AI: The Future of Enterprise Data.”
This is especially true when data elements are dispersed across multiple lines of business organizations or sourced from external sites containing unstructured content. One way to address this is knowledge graph technology. It can remediate these challenges and open up new realms of opportunity not possible before with legacy technologies.
The Financial Industry Business Ontology (FIBO) is a good example of a semantically-modeled knowledge graph for finance. Semantic graphs can be further enriched with probabilistic associations from machine learning and data mining algorithms.
Knowledge graphs also offer better customer support, risk management, regulatory compliance and technology asset management.
Melody K. Smith
Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.
