To advance from traditional data warehousing to dynamic data warehousing requires a low-latency environment, not just a large atomic data warehouse. Most of the capabilities required to get from vanilla data warehousing to near real-time, on-demand data warehousing are implemented by the proprietary data warehouse vendors as workarounds to a legacy database and operating system.
The proprietary data warehouse vendors make it sound like loading inconsistent, diverse data into its atomic data store automatically rationalizes it and renders it consistent. Not so. What is required is a dynamic ecosystem that makes data warehousing as simple as front, middle and back end. The time horizon extends upstream and downstream to encompass the atomic data warehouse in an architecture designed to reduce latency at key points in the information supply chain. Key chokepoints that create delay are in-bound processing, data rationalization, closing the loop between transactional and business intelligence systems and information delivery.
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