Best Practice Report

Massive But Agile: Best Practices For Scaling The Next-Generation Enterprise Data Warehouse

June 3rd, 2009
James Kobielus, null
James Kobielus
With contributors:
Boris Evelson , Noel Yuhanna

Summary

Information and knowledge management (I&KM) professionals continue to expand the scale, scope, and deployment roles for their enterprise data warehouse (EDW) investments. Today's most demanding EDW environments support petabytes of aggregated data, trillions of records, thousands of concurrent users and queries, complex mixed-query workloads, subsecond latencies, and continuous, high-volume data loading. Information managers are adopting EDW best practices that push the scalability and performance envelope without sacrificing the agility to optimize this critical infrastructure to ever-changing analytic workloads. Some key best practices involve deploying 64-bit multicore EDW processing nodes, scaling out through shared-nothing massively parallel processing (MPP), pushing query processing to grid-enabled intelligent storage layers, applying efficient compression in the storage layer, and deploying preconfigured high-end EDW appliances.

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