Plot a Course Through the Bermuda Triangle of Enterprise Data with an Enterprise Knowledge Graph

Today’s organization demands rapid insight from increasingly hybrid, varied, and changing data. Traditional enterprise data management systems can’t keep up with this growing complexity and insights get lost somewhere in the Bermuda Triangle of data storage, data catalogs, and analytic applications. Conventional graph or relational data architectures lack the access, context, and inferencing required to meet the grueling demands for innovating and monetizing advanced analytic solutions. Data catalogs provide an inventory of information assets, however, if the catalog is disconnected from the rest of the enterprise data, you’re left with a meta-data silo. This leaves data and analytic teams constrained by architectural limitations for highly scalable, discovery-style analysis in relation to business problems.

Data fabrics have emerged as a modern solution to address these data needs. An Enterprise Knowledge Graph is the key enabling ingredient to a data fabric. As a unified graph data model enriched with logical definitions, it provides a flexible data layer that dynamically weaves together data across the organization. With an Enterprise Knowledge Graph, you can connect to data regardless of where it’s stored, bring to life your data catalog, and empower your data and analytics teams with the data and insights they need, faster.

Speaker: Michael Grove

Michael is SVP of Engineering and Co-Founder at Stardog, where he manages their world-class engineering organization and helps shape the direction of the Stardog Enterprise Knowledge Graph. He has over 15 years of experience in the AI, Semantic Technology, and Graph Database fields. Prior to Stardog, Michael performed research on the use of graph-based technologies in pervasive computing environments while at Fujitsu Labs of America. Michael is a graduate of the University of Maryland in Computer Science and an alumnus of its MINDLAB, a seminal research group in Semantic Web technology.