4 Ways to Improve Your Big Data Analytics Stack ROI During COVID-19

Presented by

Kirk Lewis

About this talk

Supply chain and logistic challenges due to the global COVID-19 outbreak are making it difficult for companies to address their growing big data capacity needs and purchase and provision more servers as needed. Many organizations are addressing these issues by expediting the use of cloud services, but this can get costly if the infrastructure is not optimized. A better solution is to improve performance and get more out of your existing infrastructure. Even the most experienced IT operations teams and capacity planners can’t manually tune every application and workflow. The scale—thousands of applications per day and a growth rate of dozens of nodes per year—is too large for manual efforts. There’s a better way: Automatic capacity optimization eliminates manual tuning and allows you to run 30-50% more jobs on your existing Hadoop or Spark clusters. This webinar discusses four specific ways to automatically tune and optimize cluster resources, recapture wasted capacity, and improve your big data analytics stack ROI—on-premises or in the cloud.
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Pepperdata is the Big Data performance company. Fortune 1000 enterprises depend on Pepperdata to manage and optimize the performance of Hadoop and Spark applications and infrastructure. Developers and IT Operations use Pepperdata solutions to diagnose and solve performance problems in production, increase infrastructure efficiencies, and maintain critical SLAs. Pepperdata automatically correlates performance issues between applications and operations, accelerates time to production, and increases infrastructure ROI. Pepperdata works with customer Big Data systems on-premises and in the cloud.