The data warehouse is a database containing data from multiple operational systems that has been integrated, aggregated, and structured so that it can be used to support the analysis and decision-making process of a business.
Is all the information needed to run your business available when it's needed, in the form in which it's needed, and in sufficient detail and with accuracy to base decisions upon? Or, do two users arrive at a meeting with reports that don't match? One thinks sales for March are $500 million, and another says they're $524 million. After much analysis, you determine that different data has been used to calculate the sales in each report, and you spend considerable time trying to figure out why and correcting the problem.
Does your company have multiple systems for the same function—the old inventory system and the new one you just spent millions of dollars building? Do you need to get data from both of these to combine for reporting purposes? How well is this working? Do users need to understand the differences between the two systems to query them on line? If this requires custom programming, do you still have an application backlog?
Do you have sufficient historical detail for analysis purposes? How many months of history are you able to keep on line? Did you save the right level of detail? Did you even save all of the historical data? Are you able to analyze the sales for each product for each geographic region before and after a major reorganization of the sales force reporting structure? Data warehouses are built to help address these types of problems.