Best Practices for Big Data Analytics in Hadoop

Many data scientists and analysts do not have a deep understanding of Hadoop, so they struggle with solving their analytics problems in a distributed environment. Distributed algorithms are not always easy and intuitive and there are a lot of different approaches. This session helps to organize approaches and help you select the right approach for the task. Join us to learn:

  • Pros and cons of different approaches of analytics on Hadoop
  • Specific use cases that are a good match to one or another approach

Prekopcsák Zoltán
VP Big Data, RapidMiner

Prekopcsák Zoltán is the Vice President of Big Data at RapidMiner, the leader in Modern Analytics. Previously, he was co-founder and CEO of Radoop, before its acquisition by RapidMiner. Zoltan has experience in data-driven projects in various industries including telecommunications, financial services, e-commerce, neuroscience, and many more. Previously, he was a data scientist at Secret Sauce Partners, Inc. where he created a patented technology for predicting customer behavior. Zoltan has been a lecturer at Budapest University of Technology and Economics, his alma mater, with a focus on big data and predictive analytics. He has dozens of publications and is a regular speaker at international conferences.