We are at the juncture of a major shift in how we represent and manage data in the enterprise. Conventional data management capabilities are ill equipped to handle the increasingly challenging data demands of the future. This is especially true when data elements are dispersed across multiple lines of business organizations or sourced from external sites containing unstructured content. Knowledge Graph Technology has emerged as a viable production ready capability to elevate the state of the art of data management. Knowledge Graph can remediate these challenges and open up new realms of opportunities not possible before with legacy technologies.
This presentation will describe the operational capabilities and benefits of Knowledge Graph technology: “The Future of Enterprise Data". We will discuss how ontologies are the way forward to better represent enterprise definitions and data. The Financial Industry Business Ontology (FIBO) will be described as an exemplar of a semantically modeled knowledge graph for finance. We will describe how semantic graphs can be further enriched with probabilistic associations from machine learning and data mining algorithms. We will discuss the evolution of data from strings and numbers, to first class semantic objects to distributed representations of concept embeddings in vector space. We will also describe how Knowledge Graph technology can provide a layer of “knowledge” over legacy data structures to obtain maximum understanding of data inventory and provide the foundational building blocks for powerful data catalogs and hubs. Knowledge Graph also positions organizations to better support customer 360, risk management, regulatory compliance, technology asset management and many other use cases.