BI applications in a variety of areas, such as pricing, manufacturing, yield management, fraud detection, supply chain planning and call-center management, can help decrease the latency between data capture and when it's available for analysis. That can only be good for business.
This demand for real-time processing hit the data warehousing community where it hurt. Call it collateral damage: As data volumes have grown, so has the difficulty involved in loading massive, sometimes multiterabyte, extracts into enterprise data warehouses. Most systems need to go offline for periods of time before the updated state is finished and BI tools can have at the data.
Moreover, data warehouses have been gradually moving from monthly to weekly update schedules. More than one daily update is currently considered "right-time" in many shops--that is, close enough to real-time. The result? As BI plays a more operational role, downtime leaves businesses vulnerable.
To speed up the process, companies are turning to active data-warehouse approaches that include trickle feeding the system smaller updates rather than updating in one big lump. Others are changing their architectures to include middle-tier servers that function much like an application or transaction server to manage data feeds and play query traffic cop.
Enterprise data warehouse specialist Teradata, now in the process of splitting off from parent company NCR, cites customers such as Continental Airlines and Harrah's Entertainment that use active concepts with centralized warehouses to drive real-time customer intelligence, letting them make offers or knowledgeably respond to customers' behavior when they're on the line or playing at one of its gaming establishments.
