Your organizational database is only as good as the strategic data you can extract from it. Do customers who buy breakfast cereal typically buy bananas as well? Is there a correlation between rainfall in a particular region and the prevalence of a particular illness there? Data Mining with Microsoft SQL Server 2000 Technical Reference shows how to use Microsoft's analysis tools for large databases. Author Claude Seidman offers advice on the data-modeling engineering process as a whole, including designing strategies likely to yield meaningful results, designing data warehouses, growing decision trees, spotting clusters and anomalies in data, and automating mining processes with code.
Despite its designation as a reference, this book is largely a tutorial — you'll refer to it for advice on how to make Analysis Services do something in particular. Seidman uses a classic and effective tutorial technique, sticking with an example throughout the book and adding to previous examples as he explores additional aspects of Microsoft data mining. His illustration involves identifying edible mushrooms, based on a database of facts about known mushrooms, and he's combined how-to prose with screen shots and accumulated wisdom to great effect. If your organization has gone with Microsoft SQL Server 2000 for data storage, read this book for advice on knowledge extraction.