Sep 23–26, 2019
Shirshanka Das

Shirshanka Das
Principal Staff Software Engineer and Architect, LinkedIn

Shirshanka Das is a principal staff software engineer and the architect for LinkedIn’s analytics platforms and applications team. He was among the original authors of a variety of open and closed source projects built at LinkedIn, including Databus, Espresso, and Apache Helix. He is currently working with his team to simplify the big data analytics space at LinkedIn through a multitude of mostly open source projects, including Pinot, a high-performance distributed OLAP engine, Gobblin, a data lifecycle management platform for Hadoop, WhereHows, a data discovery and lineage platform, and Dali, a data virtualization layer for Hadoop.

Sessions

2:05pm2:45pm Wednesday, September 25, 2019
Location: 1A 23/24
Secondary topics:  Data quality, data governance and data lineage, Media and Advertising
Shirshanka Das (LinkedIn), Mars Lan (LinkedIn)
How do you scale metadata to an organization of 10,000 employees, 1M+ data assets and an AI-enabled company that ships code to the site three times a day. We describe the journey of LinkedIn’s metadata from a two-person back-office team to a central hub powering data discovery, AI productivity and automatic data privacy. Different metadata strategies and our battle scars will be revealed! Read more.

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