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Organizations need to gain deeper insights to drive their future business success and stay competitive in a faster-paced market. Insights which can only be produced from analysis of large, diverse datasets, driving a need for extreme speed and scale.

Cloudera Data Warehouse is an enterprise solution for modern analytics on an exponentially growing volume of data. It provides multiple SQL engines that are best suited for different analytics use cases:

  • Hive on Tez for huge & long-running batch jobs

  • Impala & Hive LLAP for interactive queries for datasets up to petabyte-scale

  • Spark SQL for in-memory self-service data exploration

  • The architecture & best practices for SQL engine configuration

  • The capabilities of multiple SQL engines

  • How to identify the right SQL engine for the right workload

  • Ways to optimize the performance of SQL engines

  • Real-world SQL example use cases & related SQL engines


Solutions Engineer

Sagar Kewalramani


Sagar Kewalramani is a Strategic Solutions Engineer, where he helps customers install, build, secure, optimize & tune their Hadoop clusters. He also helps new customers transition to Hadoop platform and implements their initial use cases. Sagar has worked with customers from all verticals, including Banking, Manufacturing, Healthcare, Retail& more. He has wide experience in building business use cases, high volume real-time data ingestion, transformation and movement, and data lineage and discovery. He has led to the discovery and development of big data and machine-learning applications to accelerate digital business and simplify data management and analytics. He has spoken in multiple Hadoop & Big Data Conferences including Oreilly Strata.

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