Developing an Advanced Analytics Capability for Knowledge Graph Solutions
Developing an Advanced Analytics Capability for Knowledge Graph Solutions


Enabling the Data Lake for scalable and extensible analytics with the ultimate goal of developing a learning system is rapidly taking shape for the Enterprise. Until recently big data was focused on processing massive amounts of simple, flat data. But now, there is a requirement to fuse complex data to create more intelligent analytic frameworks to achieve better business decisions. Adding advanced analytics to a Data Lake to create a scalable knowledge-based analytics platform for pattern recognition, classification, predictive modeling, and simulations is rapidly developing with use cases in Fraud Detection, Healthcare, ECommerce, Intelligence, and more.

During the presentation we will describe analytic capabilities as part of an intelligent Data Lake approach that includes several Artificial Intelligence techniques as well COTS software tools for analytics and visualization. We will also describe the commercial applicability to several domains along with demonstrations.


Dr. Jans Aasman started his career as an experimental and cognitive psychologist, earning his PhD in cognitive science with a detailed model of car driver behavior using Lisp and Soar. He has spent most of his professional life in telecommunications research, specializing in intelligent user interfaces and applied artificial intelligence projects. From 1995 to 2004, he was also a part-time professor in the Industrial Design department of the Technical University of Delft. Jans is currently the CEO of Franz Inc., the leading supplier of commercial, persistent, and scalable Graph database products that provide the storage layer for powerful reasoning and ontology modeling capabilities for Cognitive Computing applications.

Dr. Aasman has gained notoriety as a conference speaker at such events as Smart Data, NoSQL Now, Semantic Technologies Conference, International Semantic Web Conference, Java One, Linked Data Planet, INSA, GeoWeb, AAAI, Enterprise Data World, STIDS, and DEBS to name a few.

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