By Pierre Bonnet
In an more and more electronic financial system, gaining knowledge of the standard of information is an more and more very important but nonetheless, in such a lot enterprises, a substantial activity. the need of higher governance and reinforcement of foreign ideas and regulatory or oversight constructions (Sarbanes Oxley, Basel II, Solvency II, IAS-IFRS, etc.) imposes on businesses the necessity for higher transparency and higher traceability in their info.
all of the stakeholders in a firm have a job to play and nice profit to derive from the final objectives right here, yet will continually flip in the direction of their IT division looking for the solutions. notwithstanding, nearly all of IT structures which have been built inside companies are overly complicated, badly tailored, and in lots of situations out of date; those platforms have usually turn into a resource of knowledge or approach fragility for the company. it's during this context that the administration of ‘reference and grasp info’ or grasp information administration (MDM) and semantic modeling can intrude with a view to straighten out the administration of information in a forward-looking and sustainable manner.
This publication indicates how corporation executives and IT managers can take those new demanding situations, in addition to the benefits of utilizing reference and grasp information administration, under consideration in answering questions comparable to: Which facts governance capabilities can be found? How can or not it's higher aligned with enterprise rules? what's the go back on funding? How will we examine intangible IT resources and information? What are the foundations of semantic modeling? what's the MDM technical architecture? In those methods they are going to be larger capable of bring on their duties to their businesses, and place them for progress and strong information administration and integrity within the future.
Chapter 1 a firm and its information (pages 1–36):
Chapter 2 Strategic points (pages 37–56):
Chapter three Taking software program applications under consideration (pages 57–67):
Chapter four go back on funding (pages 69–85):
Chapter five MDM adulthood degrees and Model?Driven MDM (pages 87–107):
Chapter 6 facts Governance features (pages 109–132):
Chapter 7 Organizational features (pages 133–149):
Chapter eight The Semantic Modeling Framework (pages 151–185):
Chapter nine Semantic Modeling approaches (pages 187–214):
Chapter 10 Logical information Modeling (pages 215–231):
Chapter eleven association Modeling (pages 233–246):
Chapter 12 Technical Integration of an MDM process (pages 247–266):
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Additional resources for Enterprise Data Governance: Reference & Master Data Management, Semantic Modeling
2. Context management Companies work in networks at the international level or use multiple distribution channels. This ecosystem gives rise to a number of different management contexts, also called use contexts. From then on, an IT system cannot limit itself to working in a fixed context at the time of its design, in the context of the company that is its owner. It must adapt to the variations brought about by each of the different use contexts. For example, the commercial conditions of a loan are personalized depending on whether it is proposed by a given distributor, sales channel or even a country, etc.
The MDM approach is situated in this dynamic of the re-appropriation of data, rules and, finally, processes. MDM is not uniquely applied to answer data governance needs. It must act as a sustainable foundation at the time of the addition of rules and processes repositories. If the MDM design fails, it cannot fulfill this role and the improvement of the transparency of the information system is incomplete. PART ONE The MDM Approach Chapter 1 A Company and its Data This first chapter is dedicated to the role of data governance within companies and will enable us to make a clear definition of it.
This business orientation places the functions of this tool beyond technical data administration, profiting a real reference and master data governance. Business users assume operational responsibilities themselves, including data entry, managing rights, creating versions of data, having autonomous access to the audit trail, etc. IT experts still need to be involved but at the discretion of business users who decide the delegation levels of data governance that they wish to share. 2. Beyond MDM The implementation of a reference and master data repository is the first stage in the transformation of IT.