Enterprise Application Integration and Active Data Warehousing

Zusammenfassung

There was a time that data warehouse implementations were relatively isolated within the IT infrastructure of an organization. Data extract programs snuck out in the middle of the night or over a weekend to steal away with data from the opera­tional systems and load it into the informational repository (data warehouse). A select group of knowledge workers (usually in marketing, finance, strategic plan­ning, etc.) had access to this information for reporting and analysis, but the re­quirements for connectivity to large numbers of users outside the corporate ivory tower and interoperability with production systems were minimal With the expanded scope of successful data warehouses to encompass tactical decision making in addition to traditional decision support applications (cf. Brobst, Rarey 2001), the need for better integration into the mainstream of IT infrastructure has become essential. As a result, Enterprise Application Integra­tion (EAI) has emerged as a critical component in the architecture of advanced data warehouse implementations. When properly deployed, EAI provides a vehi­cle for transitioning from back office decision making to tactical decision support on the front-lines to impact execution of the enterprise strategy. EAI plays a parti­cularly important role when implementing the extreme data freshness service levels required for Active Data Warehousing