Qubole Executive to Speak at StampedeCon in St. Louis
Shrikanth Shankar, Head of Engineering at Qubole, Will Present Techniques to Optimize Hadoop in the Cloud at Big Data Event on July 30th
Palo Alto, CA (PRWEB) July 29, 2013
Qubole™, a provider of the next generation Cloud Big Data platform, is proud to announce that its Head of Engineering, Shrikanth Shankar, will speak at StampedeCon in St. Louis, Missouri on July 30th.
Shrikanth’s presentation, titled “Cloud-Friendly Hadoop and Hive”, will take place on Tuesday, July 30, 2013 at 1:30 PM. In his presentation, Shrikanth will discuss how to optimize Hadoop and its related frameworks to perform in the Cloud even better than in the datacenters for which they were originally designed for.
Following a successful live chat on Twitter on July 10, hosted by StampedeCon founder Gary Stiehr and featuring Shrikanth Shankar, both are excited for the Big Data event.
“In our second year, StampedeCon has grown faster than we had even hoped. We are looking forward to having Shrikanth and all of our experts here in St. Louis for the conference,” said Stiehr.
Shrikanth Shankar is the Head of Engineering at Qubole. Previously, Shrikanth worked at Oracle for over a decade, rising to become Director of Development in the BI team.
Shrikanth was one of the leaders of the Oracle Exalytics effort and helped drive the product from conception to release. Prior to that, Shrikanth was on Oracle’s database team in the SQL/DSS group, where he made significant contributions to many different portions of the Oracle stack, ranging from partitioning, SQL optimization, and SQL/parallel execution all the way to indexing and data layers.
Qubole provides a managed Big Data service that makes it simple to prepare, integrate and explore Big Data in the cloud. Founded by the creators of Apache Hive and ex-Facebook’s data infrastructure team, Qubole is trusted by the largest brands in social media, online advertising, gaming and other data-intensive companies.
Qubole Data Service (QDS) provides a software-as-a-service solution for Big Data teams. Running on a fast, auto-scaling Hadoop cluster with built-in data connectors and a graphical user-interface for Hive, Pig, Oozie and Sqoop, QDS makes it easy to inspect data, author and execute queries, and convert queries into scheduled jobs.
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