We’re kicking off the year at our new partner venue, Microsoft Reactor!
Apache Spark™ is the dominant processing framework for big data. Delta Lake adds reliability to Spark so your analytics and machine learning initiatives have ready access to quality, reliable data. This session covers the use of Delta Lake to enhance data reliability for Spark environments.
The role of Apache Spark in big data processing
Use of data lakes as an important part of the data architecture
Data lake reliability challenges
How Delta Lake helps provide reliable data for Spark processing
Specific improvements that Delta Lake adds
The ease of adopting Delta Lake for powering your data lake
Chris Hoshino-Fish is a Solutions Architect at Databricks. Chris is an active member of the Performance Subject Matter Expert group and a former Principal Consultant focused on Data Engineering, working with several Fortune 500 Databricks customers. Prior to Databricks, Chris worked for an adtech company as a data engineer managing pipelines using Apache Spark for 3.5 years. Chris has a B.A. in Computational Mathematics from the University of California, Santa Cruz.
-- we'll open the floor for the rest of the meetup to the lightning talks proposed in the comments!