The book deals extensively with one of the most critical elements in data warehouse design: the problem of how to handle time in the model. He examines many different roles that time plays in the model, including its role in the construction of dimensions.

The crux of his analytical efforts come with the introdution of his “Dot Modeling” method. This method provides a simple, but highly useful, conceptual framework for generating the logical model of the data warehouse. It also gives explicit support for handling most of the time-related issues. A major added benefit is that the basic Dot Modeling constructs are far simpler yet more complete than standard Entity/Relationship modeling diagrams, which makes it a joy to use with end users, who are able to construct complete and easy to comprehend data models without being required to learn any arcane Parent/Child terminologies or be dragged down into a discussion of the pros and cons of a Snowflaked model.

The rest of the book covers many other essentials of data warehouse construction, including physical implementation issues, an excellent discusion on the business justification for the project and its importance for success, and project management suggestions.

Enjoy this great book!

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Providing the tools and techniques necessary for finding errors and fraud in audits, this guide for auditors looking to better validate their Microsoft Excel spreadsheets provides techniques for performing a risk assessment and gathering spreadsheet and other data from company systems. Performing audit data analysis using data and analytical management functions and pinpointing the common errors in spreadsheets with focused Excel tests is discussed, as are the best practices for error and fraud prevention when developing spreadsheets. This reference is fully updated to reflect Excel 12.


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