Maintaining Enterprise Data Warehouses in a Changing Big Data Landscape

Today’s modern enterprise data warehouse (EDW), which has been in existence for more than 20 years, faces a growing set of challenges. The platform must incorporate data integration, quality, and governance effectively.

However, not many have. The EDW is the highest cost platform in the world for running ETL and growing workloads have necessitated continuous expansion of expensive capacity while lowering service levels for mission-critical analytics and reporting. Lack of meaningful data quality and data governance means that “garbage in and garbage out” has become an accepted standard for analytics and reporting.

DBTA recently held a webinar with Rob Utzschneider, worldwide technical sales leader, IBM’s information integration and governance business, who addressed these growing EDW challenges and explain how EDW Offloading to Apache Hadoop can make it possible to effectively incorporate data integration, quality, and governance at a significant cost reduction.

EDW faces growing challenges that include processing capacity and costs For ETL, EDW historically used as a repository for all data, EDW is unable to monetize new sources of data, most EDWs do not address data quality issues, and most EDWs do not address data governance issues.

EDW offloading can address these issues by:

  • Offloading costly ETL processes to Hadoop Data Lake
  • Archiving data away from the EDW
  • Capturing, storing, and monetizing more data as well as new sources of data
  • Implementing data quality as part of the EDW offloading process
  • Implementing data governance as part of the EDW offloading process

IBM offers the most comprehensive and integrated enterprise data integration, quality, and governance solution for EDW offloading, Utzschneider said.

According to Utzschneider, IBM can:

  • Leverage existing developer skills and assets
  • Realize a productivity gain over hand coding
  • Shared nothing, massively parallel processing architecture
  • Build a job once and run anywhere
  • Implement enterprise data quality as part of EDW offloading
  • Implement enterprise data governance for EDW offloading

An archived on-demand replay of this webinar is available here.