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, focusing on five most popular issues related to data tools and productivity and sharing best practices for solving them.
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.
Deepak Tiwari is the head of product management for data at Lyft, where he’s responsible for the company’s data vision as well as for building its data infrastructure, data platform, and data products. This includes Lyft’s streaming infrastructure for real-time decision making, geodata store and visualization, platform for machine learning, and core infrastructure for big data analytics. Previously, he was a product management leader at Google, where he worked on search, cloud, and technical infrastructure products. Deepak is passionate about building products that are driven by data, focus on user experience, and work at web scale. He holds an MBA from Northwestern’s Kellogg School of Management and a BT in engineering from the Indian Institute of Technology, Kharagpur.
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