SUMMARY

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I have a theory, which is that data warehousing has always been about customer relationships. It's just that previously we didn't entirely make the connection, because, in the early days, CRM had not really been recognized as any kind of discipline at the systems level. The advent of CRM has put the spotlight firmly back on data warehousing.

Data warehouses provide the technology to enable us to perform customer relationship analysis. The management of the relationship is the value that is added by the business. This is the decision-making part. The warehouse is doing what it has always done, providing decision support. That is why this book is about supporting customer relationship management.

In this chapter we have been looking at some of the design issues and tried to quantify and rationalize some aspects of data warehouse design that have been controversial in the past. There are good reasons for using dimensional schemas, but there are cases where they can work against us. The best solution for CRM is to use dimensional models where they absolutely do add value, in modeling customers' behavior, but to use more conventional approaches when modeling customers' circumstances.

Toward the end of the chapter we developed a general conceptual model (Figure 3.12) for a customer-centric data warehouse. We will develop this model later on in this book by applying some of the needs of our case study, the Wine Club.

Firstly, however, the awfully thorny subject of time has to be examined.

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