Even the full title of this book falls short in conveying the principal value of its content, namely the development of a design methodology based on capturing reporting requirements as data stories.

The book is organized into two parts. The first part, comprising five chapters, introduces the original BEAM* method that integrates event requirements with data modeling. The most valuable contribution is the integration of data stories (as exemplary data samples) with an interrogation framework that uses the “7Ws” (really 5 Ws and 2 Hs): who, what, when, where, how many, why, and how. This produces a pattern that enables dimensional thinking during data requirements elicitation, developed in chapter 2, “Modeling Business Events.” Furthermore, the obtained systematic data samples lead to explicit recognition of hierarchies within business dimensions, discussed in chapter 3. Chapter 4 uses an event matrix to model business processes by associating related events to dimensions, while chapter 5 explains the modeling of star schemas, in the agile manner (profiling data, sprint planning, and schema design and documentation).

The rest of the book (Part 2) is a trove of practical advice, in the form of dimensional design patterns, complementing a general method with specific recurring solutions in a condensed but well-illustrated form. Chapter 6 lists several basic WHO (people and organizations) and WHAT (product and services) patterns. Chapter 7 covers WHEN and WHERE (time and location) patterns, chapter 8 discusses HOW MANY patterns for performance fact tables and flexible measures, and chapter 9 addresses WHY and HOW design patterns for cause and effect. Of the three appendices, Appendix B is of most interest, as it presents a legend for the use of BEAM* notation, as well as short codes that can be used during quick data sample capture on interviews during requirements elicitation.

The book’s primary contribution is a hands-on approach to data warehouse and data mart requirements. The text is extensively used by the authors in their workshops for professionals, but it can be readily recommended to computer science and information systems students. It was field tested in the past two years in a number of data warehouse design classes, and was very well received; most students enthusiastically indicated that it was a fast way to grasp the significance of requirements and an eye-opener in justifying and validating star schema designs.

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