MASTER DATA MANAGEMENT AND DATA GOVERNANCE, 2/E Review

Average Reviews:

(More customer reviews)This book is great for beginners just starting out with MDM as well as seasoned professionals. I was introduced to MDM with the first version of this book. That was not my copy, so I bought the second edition for myself.
This book covers everything MDM from architectural considerations to governance and market trends.
The book offers some really sound advice on building the business case for MDM and how to communicate that business case effectively. Listen to their advice!!!! I am an architect, purely a technical guy, but I can tell you from experience without the backing of the business your project will be squashed.
The book covers the technical aspects of implementation in great detail. This book will give you the insight you need to fully understand the complexities of an MDM project. There are a ton of vendors out their claiming to have a magic install of MDM available for purchase, but the truth is they just do not exist. MDM is a process with many steps involved, not a product.
All in all if you are involved or getting involved with MDM this is the book to read.


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The latest techniques for building a customer-focused enterprise environment
"The authors have appreciated that MDM is a complex multidimensional area, and have set out to cover each of these dimensions in sufficient detail to provide adequate practical guidance to anyone implementing MDM. While this necessarily makes the book rather long, it means that the authors achieve a comprehensive treatment of MDM that is lacking in previous works." -- Malcolm Chisholm, Ph.D., President, AskGet.com Consulting, Inc.
Regain control of your master data and maintain a master-entity-centric enterprise data framework using the detailed information in this authoritative guide. Master Data Management and Data Governance, Second Edition provides up-to-date coverage of the most current architecture and technology views and system development and management methods. Discover how to construct an MDM business case and roadmap, build accurate models, deploy data hubs, and implement layered security policies. Legacy system integration, cross-industry challenges, and regulatory compliance are also covered in this comprehensive volume.

Plan and implement enterprise-scale MDM and Data Governance solutions
Develop master data model
Identify, match, and link master records for various domains through entity resolution
Improve efficiency and maximize integration using SOA and Web services
Ensure compliance with local, state, federal, and international regulations
Handle security using authentication, authorization, roles, entitlements, and encryption
Defend against identity theft, data compromise, spyware attack, and worm infection
Synchronize components and test data quality and system performance

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Enterprise Data Governance Master Data Management and Semantic Modeling: MDM Review

Average Reviews:

(More customer reviews)I would say the work of the MDM Alliance Group (MAG) as a whole is a 5 star rating. This book however is not. I have been following the work of the MAG for a while now. I have downloaded and read all their papers they make available online, and quite frankly, they are more thorough.
There are several places in the book where the author says we don't have room in the book for this, so go download our whitepaper. The entire reason for writing a book is to expand on a topic, not provide an abstract of previous work. Almost every chapter left me with the feeling that is was incomplete.
I paid the full $80 price tag for this. I would recommend it if the price tag come down to $30, if you want an overview of how MAG views the world of MDM, or if you are new to MDM and want an overview. Don't buy it for the semantic modeling unless you just want an overview. Go download the whitepapers from the MAGs site.


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In an increasingly digital economy, mastering the quality of data is an increasingly vital yet still, in most organizations, a considerable task. The necessity of better governance and reinforcement of international rules and regulatory or oversight structures (Sarbanes Oxley, Basel II, Solvency II, IAS-IFRS, etc.) imposes on enterprises the need for greater transparency and better traceability of their data.
All the stakeholders in a company have a role to play and great benefit to derive from the overall goals here, but will invariably turn towards their IT department in search of the answers. However, the majority of IT systems that have been developed within businesses are overly complex, badly adapted, and in many cases obsolete; these systems have often become a source of data or process fragility for the business. It is in this context that the management of 'reference and master data' or Master Data Management (MDM) and semantic modeling can intervene in order to straighten out the management of data in a forward-looking and sustainable manner.

This book shows how company executives and IT managers can take these new challenges, as well as the advantages of using reference and master data management, into account in answering questions such as: Which data governance functions are available? How can IT be better aligned with business regulations? What is the return on investment? How can we assess intangible IT assets and data? What are the principles of semantic modeling? What is the MDM technical architecture? In these ways they will be better able to deliver on their responsibilities to their organizations, and position them for growth and robust data management and integrity in the future.

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