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There are several ways to make the transition to real-time business intelligence (BI).
One approach to switch to real-time business intelligence is to make the data warehouse real-time, loading it in concert with operational structures and minimizing operational business intelligence. This is simple in concept. However, making data warehouses real-time can be an extremely complex challenge. Operational systems need to cooperate with this vision by not being so fragile that they break with intra-day extracts. The data warehouse environment needs to be efficient to the point where the requested extracts are kept to a minimum. This is not always the case, so real-time remains a challenge. Service-oriented architecture has increasingly helped allow operational queries, but extracts remain a challenge.
Sometimes, however, the simplicity and value-add of a real-time data warehouse can prove to be so enormous that a company can choose to actually replace its operational system with one that is more "real-time data warehouse friendly." That's the second approach. Generally, these are systems that can tolerate extracts while also performing real-time operations. The irony is that many of these modern enterprise resource planning (ERP) systems provide much more analytics than previous ones and also control many of the functions that previously were the domain of the data warehouse. Consequently, some companies have found themselves in the enviable position -- but still at an intersection -- of having analytical abilities both in operations as well as in a real-time enabled data warehouse.
Putting that aside for the moment, most shops need to choose generally where analytics and business intelligence will prevail, and give the appropriate attention to operational BI as a result. I do not believe a shop can ignore operational business intelligence any longer. However, the emphasis of where the majority of BI occurs is in question -- in the data warehouse or in the operational arena.
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