Preparing for Dynamic Data Warehousing

Webinar Abstract
The majority of data warehouse (DW) and business intelligence (BI) deployments today are designed for updates on a 24-hour cycle. In other words, most data integration routines load a data warehouse in nightly batch processing, and most reports are likewise refreshed overnight after the data warehouse has been updated. While this is a tried-and-true method that all DW and BI deployments should support, many user organizations also need to integrate data into their warehouses and refresh reports multiple times a day, so they can embrace time-sensitive business methodologies like zero latency, performance management, just-in-time inventory, and so on. The challenge is to extend a traditional data warehouse so it's also a dynamic data warehouse that integrates and delivers information in real time or on demand.

You will learn:

  • How to prepare for dynamic data warehousing, plus related practices, like operational BI and on demand data integration
  • What adjustments must be made to data integration routines, interfaces, reports, data models, and so on to make them conducive to dynamic data warehousing
  • Adjustments to business processes and operational applications, so they fully leverage dynamic data warehousing
  • Which data, reports, and users require a dynamic treatment (not all do)
  • Other requirements of dynamic data warehousing, like scaling to larger user and report counts, increased data synchronization, high availability for the DW, intense service level agreements, and even tighter interoperability with operational systems

Philip Russom, Ph.D.

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