SmartBiz IT Research Library

Extract, transform and load (ETL) has traditionally been one of the most popular data integration methods for business intelligence and data warehousing. But as more organizations move toward near-real-time applications, we wondered -- how real time can ETL really get? Can ETL support the requirements of near-real-time applications -- and what should organizations consider when designing these systems and processes? In this podcast, learn when and how ETL can effectively support near-real-time requirements and find out more about the benefits and drawbacks of using ETL for these kinds of projects, from Mark Whitehorn, an expert consultant with real-world experience and insight.

In this 10-minute podcast, appropriate for BI-savvy IT and business professionals, listeners will:

• Learn the benefits and drawbacks of using extract, transform and load (ETL) as the primary data integration method for near-real time applications
• Hear more about the key issues to think about when considering this approach -- and find out whether it's the appropriate method for your needs
• Get expert insight into the potential costs involved with deploying ETL in near-real-time situation

Interested in this topic, but prefer alternative content formats? Try:

• Webcast with PowerPoint slides: Optimizing ETL for demanding data environments