Semantic Knowledge Graphs are the Governance Architecture of the Future

Currently, due to legacy IT environments, data governance is often an afterthought.  It is an add-on layer retrofitted after data sources and applications are introduced in the enterprise. This “rear mirror view” approach means that connecting and capturing necessary information, at the right levels, is very difficult.  Organizations spend a lot of money and time on implementing data governance solutions, but practical results are often modest.

Information that is necessary to manage enterprise data as an asset requires connecting different viewpoints and stakeholders – a natural fit for a knowledge graph. Knowledge graphs provide the basis for a  forward looking approach that data owners, data consumers, data stewards, architects, engineers,  and all data stakeholders can adopt and utilize in their designs, development, and operations.  With a knowledge graph approach, ‘to be governed’ assets can be dynamically modeled and the necessary metadata collected at any time as an ongoing part of any enterprise system (as it evolves from design to in-use) instead of only ‘after the system.’

In this webinar we show how TopBraid EDG delivers adaptive enterprise data governance, with capabilities that let enterprise data governance implementations:

  • Take back control of the user experience
  • Remove the barriers to interoperability
  • Connect structured and unstructured information intelligently
  • Enable model-driven JSON APIs
  • Provide extensibility through dynamic introspection

Ready to Get Started?

Get in touch today to learn how to improve semantic data governance for your enterprise.