Presented By O'Reilly and Cloudera
Make Data Work
September 25–26, 2017: Training
September 26–28, 2017: Tutorials & Conference
New York, NY
Mark Grover

Mark Grover
Product Manager, Lyft

@mark_grover

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.

Sessions

1:30pm5:00pm Tuesday, September 26, 2017
Secondary topics:  Architecture
Jonathan Seidman (Cloudera), Gwen Shapira (Confluent), Mark Grover (Lyft)
Average rating: ****.
(4.11, 9 ratings)
Using Customer 360 and the IoT as examples, Jonathan Seidman, Mark Grover, and Gwen Shapira explain how to architect a modern, real-time big data platform leveraging recent advancements in the open source software world, using components like Kafka, Impala, Kudu, Spark Streaming, and Spark SQL with Hadoop to enable new forms of data processing and analytics. Read more.
1:15pm1:55pm Thursday, September 28, 2017
Location: 1E 14
Mark Grover (Lyft), Jonathan Seidman (Cloudera), Ted Malaska (Capital One), Gwen Shapira (Confluent)
Average rating: ****.
(4.00, 2 ratings)
Mark Grover, Ted Malaska, Gwen Shapira, and Jonathan Seidman, the authors of Hadoop Application Architectures, share considerations and recommendations for the architecture and design of applications using Hadoop. Come with questions about your use case and its big data architecture or just listen in on the conversation. Read more.