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Enterprise Data Governance. Reference And Master Data Management Semantic Modeling

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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





  • Описание
  • 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

    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

    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

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