The amount of information stored in corporate databases is exploding exponentially. Data mining—finding meaningful patterns in all that data—can give any organization a competitive advantage. This book is the in-depth reference from Microsoft® for anyone who wants to take full advantage of the powerful data-mining features in SQL Server™ 2000. It examines the SQL Server 2000 Analysis Services architecture and shows how data mining fits into its complete suite of information-extraction technologies. Then it demonstrates how to structure and mine large databases with the algorithms included with SQL Server 2000 to find nuggets of useful information. It even shows how to create a practice data-mining model using data downloaded from a database. Coverage includes:
- INTRODUCTION TO DATA MINING: What data mining is and isn’t, plus important principles and definitions behind data-mining methodologies, including the role of data-mining models, statistics, and algorithms
- SQL SERVER 2000 ARCHITECTURE: How data mining fits into the SQL Server 2000 Analysis Services architecture and how it builds on the SQL Server 2000 relational database and its embedded online analytical processing (OLAP) engine
- DATA-MINING METHODS: How to choose the best data-mining method for the job—decision trees or clustering
- EASE OF USE FEATURES: How to use the Mining Model Wizard and the OLAP Mining Model Editor to simplify creating, training, and processing a model
- PROGRAMMING THE DATA-MINING SERVICES: How to use data-mining models and Data Transformation Services, PivotTable® Services, decision-support objects (DSO), PERL, Visual Basic®, Scripting Edition, XML, and other tools and languages to work with the data-mining engine
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Data Mining with Microsoft SQL Server 2000 Technical Reference, your organisational 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-modelling 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 organisation has gone with Microsoft SQL Server 2000 for data storage, read this book for advice on knowledge extraction. --David Wall
Topics covered: Microsoft Analysis Services, including the proper use of Data Transformation Services (DTS), PivotTable Services, Decision-Support Objects (DSO), and the Microsoft implementation of Online Analytical Processing (OLAP ).
