Graph databases are on the frontier of the NoSQL landscape, and every day new applications for graph are emerging in both consumer and enterprise technology.

The concept of the Knowledge Graph is getting a lot of airtime thanks to Google and the explosion of cognitive platforms, but what does this actually mean for engineering?

In this presentation, we will share a real framework for data engineers and architects to build a knowledge graph for the enterprise.

You will learn:

• What the enterprise knowledge graph stack looks like
• The concepts and functionality that you need to get from graph to knowledge graph
• How machine learning and the knowledge graph interact at query time
• Why any data engineer or architect should be thinking about this
• Where to start, including languages, services and first steps

Six of the eight most valuable companies in the world are using this framework to drive their data architecture and strategy; it is real. We are really excited to share our playbook for doing this in your own engineering organization and projects.

Mike Grove

Co-Founder & VP Engineering,
Stardog

Michael is VP of Engineering and Co-Founder at Stardog where he manages their world-class engineering organization and helps shape the direction of the Stardog 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.