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.
Click Here to see more reviews about: Enterprise Data Governance Master Data Management and Semantic Modeling: MDM
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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