Enterprise Data Governance Reference and Master Data Management Semantic Modeling
-
Form:Einzelkauf Download
-
Sprache:Englisch
-
eBook Format:PDF
- PDF 139,99 € ausgewählt
- ePUB 139,99 €
139,99 €
inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
Kopierschutz
Ja
Family Sharing
Nein
Text-to-Speech
Nein
Erscheinungsdatum
04.03.2013
Verlag
SybexSeitenzahl
320 (Printausgabe)
Dateigröße
3146 KB
Auflage
1. Auflage
Sprache
Englisch
EAN
9781118622407
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.
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.
Noch keine Bewertungen vorhanden
Verfassen Sie die erste Bewertung zu diesem Artikel
Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.
Kurze Frage zu unserer Seite
Vielen Dank für dein Feedback
Wir nutzen dein Feedback, um unsere Produktseiten zu verbessern. Bitte habe Verständnis, dass wir dir keine Rückmeldung geben können. Falls du Kontakt mit uns aufnehmen möchtest, kannst du dich aber gerne an unseren Kund*innenservice wenden.
zum Kundenservice