Active Data Warehousing isn’t really a buzzword. Its been in the industry for a while. Thanks to Teradata who made this buzzword popular. They called it @ctive Data Warehousing and branded the spelling.
The reason to bring back this term is because -
Teradata Corporation (NYSE: TDC), the global leader in enterprise data warehousing, announced today that Highmark Inc., the largest health insurer in Pennsylvania and one of the largest in the U.S., continues to expand its Teradata Warehouse and its multiple-terabyte information assets. The large-scale analytics expansion increases the company’s production environment and supports the shift to active data warehousing (ADW).
For newbies, here’s more about ACtive Data Warehousing from DM Review of April 2004(yep, its 4 years old enough) -
Active data warehousing is a process, not a specific technology. Teradata has popularized the term “active data warehousing,” tried to brand the spelling “@ctive data warehousing” and deserves credit for providing examples of some big, successful active data warehouses. However, if a more generic term is preferred, then “closed-loop processing” is a useful synonym, though it only partially captures the concept. Your data warehouse (DW) is active if
It represents a single, canonical state of the business (version of the truth). Too often, companies put data into a data warehouse and also store it in a plethora of other data stores. If a data warehouse must be match-merged with dependent data marts to provide needed information, then it is a potentially useful data store, but it is not active.
It supports a mixed workload. The workload of an active data warehouse will typically consist of tactical inquires executing concurrently with complex business intelligence (BI) queries and trickle updates. If the DW is used only for operational queries such as customer transactions or product inventory, it is not active.
Operational processing is driven by the DW. Active data warehouses do not exist in a vacuum. They exist in a processing loop.
The “outbound” activity goes from the data warehouse to the operational system by means of automated system mechanisms including triggers, special purpose programming interfaces, a message broker and an extract, transform and load (ETL) tool – though the ETL tool is not often used for outbound activities. If the data warehouse doesn’t deliver information automatically to operational systems, then it is not active. Manual intervention gets the job done, but the DW is not active.
It represents a closed-loop process. In particular, the data warehouse is used to optimize processing in the upstream operational or transactional system. The operational systems feed the data warehouse which, in turn, feeds back to the operational system to optimize the relevant transactional processing. The interfaces go in both directions. The data warehouse provides operational intelligence and, as active, can properly be described as driving operational processing.