Big Data, Fast Data, and Complex Data - Defining and Overcoming Challenges

Every day we speak with software engineers trying to find a productive approach for application development that requires a combination of BigData, Fast Data, and Complex Data solutions. In this presentation we will first describe when to use BigData solutions like Hadoop and Cassandra, then we will cover concepts around Fast Data solutions like in-memory graph databases, and finally we discuss use cases for Complex Data that thrive with Semantic Technologies.

The second part of this talk discusses a combined platform architecture for real time semantic entity tracking that needs the scale of Hadoop but also the speed of in-memory databases and the complexity of semantic technologies. We will discuss best practices for managing scalability solutions, ETL pipeline strategies, and complex event processing (CEP).

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 RDF database products that provide the storage layer for powerful reasoning and ontology modeling capabilities for Semantic Web applications.