Red Hat Summit 2017

This year we’re teaming up with Red Hat at Red Hat Summit to discuss analytics frameworks, and how you can get the most out of your data.

Thursday, May 4

In the beginning, there was MapReduce over HDFS analyzing clickstream data. Since the advent of modern big data, there’s been an explosion of analytics frameworks—both inside and outside of the Hadoop ecosystem. To meet the different SLAs and processing needs of multiple analytics engines, data-driven enterprises have deployed many different specialized clusters, resulting in replication of large data sets attached to multiple Hadoop clusters. A common object storage data lake (like Ceph), coupled with on-demand compute resources (like OpenShift or OpenStack), offers a more flexible alternative to faster business insights. Join Red Hat and Silicon Valley Data Science in this session to learn how to re-architect the relationship between analytics processing and big data storage; provide data scientists with flexible, cost-efficient resources for their varied analytics jobs, and feed all analytics jobs from a common object storage data lake.