After going through newly published book on Master Data Service named:Data Quality and Master Data Management with Microsoft SQL Server 2008 R2 which can be download from link:Data Quality – Master Data Management – DQ – DM – Dejan Sarka – Davide Mauri I wish I could collect and share some info on the same :
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References in Book: · 53 Microsoft SQL Server MVPs: SQL Server MVP Deep Dives (Manning, 2010) · Carlo Batini, Monica Scannapieco: Data Quality – Concepts, Methodologies and Techniques (Springer-Verlag, 2006) · Beyond SoundEx – Functions for Fuzzy Searching in MS SQL Server · Levenshtein distance on Wikipedia · Jaccard index on Wikipedia · Jaro-Winkler distance on Wikipedia · Ratcliff/Obershelp pattern recognition on National Institute of Standards and Technology · Fuzzy Lookup and Fuzzy Grouping in SQL Server Integration Services 2005 article on MSDN describing more details about Fuzzy transformations than Books Online |
Overview of book:
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.
Some Of the Key points in book Which I like most
· 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. People are prone to make errors. Sometimes our customers do not provide us with accurate and timely data. Sometimes an application has a bug and makes errors in the data. Sometimes end users unintentionally make a transposition of letters or numbers. Sometimes we have more than one application in an enterprise, and in each application we have slightly different definitions of the data. (We could continue listing data problems forever.)
· 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.
· 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.
· With three other colleagues from SolidQ, Itzik Ben-Gan, Herbert Albert, and Gianluca Hotz, we are forming a gang of four inside the company, called Quartet. It is not just unofficial group; our official duty in the company is to certify and confirm places for company parties. Our endless discussions during conferences, hikes, or time spent in pubs are an invaluable source of insight and enlightenment. Besides general help through our socializing, all three of them have made a concrete contribution to this book.
Overview of Master Data:
Master Data Services helps enterprises standardize the data people rely on to make critical business decisions. With Master Data Services, IT organizations can centrally manage critical data assets companywide and across diverse systems, enable more people to securely manage master data directly, and ensure the integrity of information over time.
Top Features
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Master data hub that provides central management of master data entities and hierarchies
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Thin-client stewardship portal that provides secure, role-based Web access to master data
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Versioning of all data entities and hierarchies
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Human workflow that notifies assigned owners by e-mail of business rule violations
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Flexible and extensible business rules that safeguard the quality of data entered in the master data hub
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Support for a broad range of hierarchy and attribute management strategies and requirements
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Comprehensive role-based security model that enables fine-grained, secure access to master data
Additional Resources
Related Sites
Whitepapers
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Defining the role of master data management in the organization: a business perspective
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Defining the role of master data management in the organization: a technical perspective
(B)usiness (I)ntelligence Mentalist 
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