The primary determinant of the size and shape of the data warehouse is the size and shape of the business problem, not the company building the system. If ever a question was squarely in the "it depends" area, this is it. Still, it is possible to make some generalizations concerning the functional dependencies on which "it depends." The dependencies include:

Let's look at some examples by way of illustration. Think of three different enterprises with $3 billion in revenue. One is a telecommunications company with 3 million customers to whom the firm wants to cross-sell and up-sell additional telecom products and services. The second is a consumer packaged goods (CPG) firm that wants to improve logistics and distribution, and reduce inventory by means of superior demand planning. The third is a high technology manufacturer (not necessarily in information technology) that wants to improve quality and manage relations with suppliers, users of its products and regulatory oversight agencies. The first will be the largest because of the amount of detailed transactional data to be aggregated. The second will be less large in terms of data, but perhaps more computationally intense and complex in terms of the calculations that need to occur to generate a multiplicity of forecasts by product. Therefore, less cost will be consumed by disk, but more will be consumed in process design. The third will probably entail even less data but will be extremely challenging in terms of how the data is to be captured, represented and evaluated as to the key performance indicators (KPIs). While the data and schema integration challenges are significant in all three cases, the third case presents special challenges requiring considerable domain expertise concerning the manufacturing processes in question. After a year of operation, the telecommunication warehouse will be 1 terabyte or more of detailed transactional data, the CPG warehouse will be a couple of hundred gigabytes of shipment and forecasting data (depending on the number of products), and the manufacturing warehouse may be 50 to 100 gigabytes. Second, vertical industry dynamics influence the business problem being addressed by the data warehouse and, in turn, influence the size and shape of the data warehouse. If an industry makes extensive use of data warehousing ­– think of retail or financial services –­ an enterprise in that vertical which does not build a data warehouse (or find a way of getting the same answers elsewhere) is at risk of incurring information asymmetries that put it at a competitive disadvantage.

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