Presented By O’Reilly and Cloudera
Make Data Work
21–22 May 2018: Training
22–24 May 2018: Tutorials & Conference
London, UK
Mark Grover

Mark Grover
Product Manager, Lyft


Mark Grover is a product manager at Lyft. Mark’s a committer on Apache Bigtop, a committer and PPMC member on Apache Spot (incubating), and a committer and PMC member on Apache Sentry. He’s also contributed to a number of open source projects, including Apache Hadoop, Apache Hive, Apache Sqoop, and Apache Flume. He’s a coauthor of Hadoop Application Architectures and wrote a section in Programming Hive. Mark is a sought-after speaker on topics related to big data. He occasionally blogs on topics related to technology.


17:2518:05 Wednesday, 23 May 2018
Data science and machine learning
Location: Capital Suite 14 Level: Intermediate
Mark Grover (Lyft), Deepak Tiwari (Lyft)
Average rating: ***..
(3.83, 6 ratings)
Sure, you’ve got the best and fastest running SQL engine, but you’ve still got some problems: Users don’t know which tables exist or what they contain; sometimes bad things happen to your data, and you need to regenerate partitions but there is no tool to do so. Mark Grover and Deepak Tiwari explain how to make your team and your larger organization more productive when it comes to consuming data. Read more.
12:0512:45 Thursday, 24 May 2018
Secondary topics:  Transportation and Logistics
Mark Grover (Lyft), Ted Malaska (Capital One)
Average rating: *****
(5.00, 6 ratings)
Many details go into building a big data system for speed, from determining a respectable latency until data access and where to store the data to solving multiregion problems—or even knowing just what data you have and where stream processing fits in. Mark Grover and Ted Malaska share challenges, best practices, and lessons learned doing big data processing and analytics at scale and at speed. Read more.