Dejan Sarka & Davide Mauri: Data Quality and Master Data Management with Microsoft SQL Server 2008 R2
Data is the key asset of any company. However, not all data is equally important. In an enterprise, we can always find the key data, such as customer data. This key data is the most important asset of a company. We call this kind of data master data.
If everyone would always insert correct data into a system, there would be no need for proactive constraints or for reactive data cleansing. We could store our data in text files, and maybe the only application we would need would be Notepad. Unfortunately, in real life, things go wrong. A good and suitable data model, like the Relational Model, enforces data integrity through the schema and through constraints. Unfortunately, many developers still do not understand the importance of a good data model. Nevertheless, even with an ideal model, we cannot enforce data quality. Data integrity means that the data is in accordance with our business rules; it does not mean that our data is correct.
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This book deals with master data. It explains how we can recognize our master data. It stresses the importance of a good data model for data integrity. It shows how we can find areas of bad or suspicious data. It shows how we can proactively enforce better data quality and make an authoritative master data source through a specialized Master Data Management application. It also shows how we can tackle the problems with duplicate master data and the problems with identity mapping from different databases in order to create a unique representation of the master data.
For all the tasks mentioned in this book, we use the tools that are available in the Microsoft SQL Server 2008 R2 suite. In order to achieve our goal—good quality of our data—nearly any part of the suite turns to be useful. This is not a beginner’s book. We, the authors, suppose that you, the readers, have quite good knowledge of SQL Server Database Engine, .NET, and other tools from the SQL Server suite.
Achieving good quality of your master data is not an easy task. We hope this book will help you with this task and serve you as a guide for practical work and as a reference manual whenever you have problems with master data.
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Courses with Dejan Sarka: Data Mining with SQL Server 2008 UK, London Jun 27-29
Advanced T-SQL Querying, Programming and Tuning for SQL Server 2005 & 2008 Slovenia, Ljubljana Jul 4-8
Master Data Management with SQL Server 2008 R2 Slovenia, Ljubljana Jul 11
Data Modeling Essentials Denmark, Copenhagen Aug 31 - Sep 2
Data Mining with SQL Server 2008 Denmark, Copenhagen Sep 5-7
Data Mining with SQL Server 2008 Austria, Vienna Sep 12-14
Advanced T-SQL Querying, Programming and Tuning for SQL Server 2005 & 2008 Austria, Vienna Dec 12-16
Detailed info about courses
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