Businesses are discovering the untapped potential of large datasets and data streams through the use of technologies for big data processing and storage. By leveraging these assets they’re creating a new generation of applications that derive value from data they used to throw away. In this presentation Ian Downard will discuss how to build operational environments for these types of applications with the MapR Converged Data Platform and he’ll walk through an example of a next-generation application that uses Java APIs for MapR Streams, Apache Spark, Apache Hive, and MapR-DB. We’ll see how these technologies can be used to join and transform unbounded datasets to find signals and derive new data streams for a financial scenario involving real-time algorithmic trading and historical analysis using SQL. We’ll also discuss how MapR enables you to run real-time data applications with the speed, reliability, and security you need for a production environment.

Ian Downard is a technical evangelist for MapR where he is focused on creating developer-friendly ways to use the MapR Converged Data Platform.

Personal Blog: http://www.bigendiandata.com

Twitter: https://twitter.com/iandownard

GitHub: https://github.com/iandow