Avoiding the Architecture Undertow: Building Lighting-Fast Queries with Blazing Fast Object Storage
Organizations are increasingly levering analytics to turn data into insights for competitive advantage. However, the architectural considerations for platforms that support large data lake deployments of analytics applications change significantly as these efforts mature beyond small scale to large scale environments. One highly successful trend is the adoption of object storage in analytics allowing data teams to be able to analyze data anywhere and everywhere. In this session we will explore how to build out an enterprise scale data lake for lightning-fast queries with blazing fast object storage.
Thomas Henson is the Senior Business Development Manager for UDS AI/Analytics. Thomas previously was an Advisory Systems Engineer and Co-Leader of the AI Spartans for the Unstructured Data Solutions Team at Dell EMC. Prior to Thomas’s time at Dell Technologies he was a Data Engineer on many different Big Data, Analytics and Artificial Intelligence projects throughout his career with a focus on distributed systems. He is proud Alumni of the University of North Alabama; where he received both his undergraduate and MBA with a focus in Computer Information Systems. Thomas lives in the Huntsville, Alabama area with his wife, Amber and two energetic children, Farrah and Tommy. In his spare time, he enjoys hanging out with family, Traeger Grills, Crossfit, running, and reading.
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