Archiving, E-Discovery, and Supervision with Spark and Hadoop - Databricks

Archiving, E-Discovery, and Supervision with Spark and Hadoop

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Today, there are several compliance use cases ‒ archiving, e-discovery, supervision and surveillance, to name a few ‒ that appear naturally suited as Hadoop workloads, but haven’t seen wide adoption. In this session, you’ll learn about common limitations, how Apache Spark helps and some new blueprints for modernizing this architecture and disrupt existing solutions. Additionally, we’ll review the rising role of Apache Spark in this ecosystem, leveraging machine learning and advanced analytics in a space that has traditionally been restricted to fairly rote reporting.

Session hashtag: #SFent7

About Jordan Volz

Jordan Volz is a Systems Engineer at Cloudera. He helps clients design and implement big data solutions using Cloudera’s Distribution of Hadoop, across a variety of industry verticals. Previously, he has worked as a consultant for HP Autonomy delivering compliance archiving, e-Discovery, and electronic surveillance solutions to regulated financial services companies, and as a developer at Epic Systems building HIPPA-compliant EMR software.