Explore fast analytics on big data in this 50-minute conference talk from GOTO Aarhus 2014. Dive into an open-source platform for in-memory distributed data processing, capable of handling datasets from 1K to 1TB without code changes. Learn about state-of-the-art predictive modeling and analytics techniques that are significantly faster than disk-bound alternatives and R. Discover how to run R expressions on tera-scale datasets and manipulate data using Scala and Python. Gain insights into the platform's coding style and API that enables seamless scaling from laptop to 100-server clusters. Examine topics such as MapReduce, data layout, chunk alignment, and Spark integration. Witness a live demo and participate in a Q&A session to deepen your understanding of this powerful big data analytics solution.