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وصف كتب مصر
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.