A leading Fortune 100 multinational investment bank was running an on-prem/private cloud Hadoop cluster which provided a data analytics platform to support its global business operations. The company was experiencing exponential growth. With the amount of ingested data doubling from year-to-year, the company faced the prospect of having to add costly compute resources at an unsustainable rate – along with associated maintenance, support, climate control, and real estate costs. The company needed to gain control of runaway IT resource spend while maintaining optimal workload performance levels and meeting business-critical SLAs. Read how they gained 30% improvement in server utilization and capacity with Pepperdata, equivalent to 100s of nodes.