LinkedIn's is the most advantageous social networking tool available to job seekers and business professionals today, with 610+ million members creating millions of posts, videos, and articles that generate tens of millions of shares, comments and likes per day. LinkedIn has leveraged this activity data to build rich interactive user-facing analytics applications like “Who Viewed My Profile”, Talent Insights, Ad Analytics and Publisher Analytics, among others. These applications are all powered by Pinot, as are internal dashboards, anomaly detection and root cause analysis platform like ThirdEye. This talk will present how Pinot has become the de-facto solution for serving analytic queries in milliseconds, ad-hoc reporting, monitoring & Anomaly Detection on multidimensional data.
Kishore Gopalakrishna is a founding engineer at a stealth mode startup. Prior to that, he was the architect at LinkedIn’s analytics infra team. Kishore is passionate about solving hard problems in distributed systems. He has authored various distributed systems such as Apache Helix, a cluster management framework for building distributed systems; Espresso, a distributed document store; Apache Pinot, a real-time distributed OLAP engine; and ThirdEye, a platform for anomaly detection and root cause analysis at LinkedIn.
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