Business users work under tight deadlines to provide answers to pressing business questions. Yet in today’s dynamic business environment, data and analytic requirements are ever changing and users never seem to have access to what they need when they need it. Even when data is available, it can be weeks or even months old and often lacks useful detail. The overstretched IT department simply can’t keep up with user demand and the backlog of requests just gets worse as data from inside the enterprise and from new social media sites like Twitter grows. While business users wait, companies miss opportunities that could have positively impacted their bottom line.

Operational business intelligence attempts to address these types of information delivery issues by allowing reporting and analysis to be performed within a very short window of time when business transactions have occurred. As the complexity of traditional data warehouse platforms makes it nearly impossible for IT departments to accommodate requests for operational BI in a timely manner, many organizations have turned to alternative approaches. Historically, in addition to replicating front-office data stores for BI purposes, organizations have achieved operational BI either through overnight batch reporting jobs run directly against their online transaction processing systems or through creating an operational data store that contains some limited history from transaction processing systems.

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