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100   $a20100415d2010      uy             0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aEnterprise data governance$b[electronic resource] $ereference & master data management, semantic modeling /$fPierre Bonnet
210   $aLondon $cISTE ;$aHoboken, N.J. $cISTE Ltd.$d2010
215   $a1 online resource (334 p.)
225 1 $aISTE
300   $aAdapted and updated from Management des donne?es de l'entreprise. Master Data Management et mode?lisation se?mantique published 2009 in France by Hermes Science/Lavoisier.
311   $a1-84821-182-1 
320   $aIncludes bibliographical references and index.
327   $aA company and its data -- The strategic aspects -- Taking into account business software -- Return on investissement -- MDM maturity levels and the model-driven MDM -- Data governance functions  -- Organisational aspects -- The semantic modelling framework  -- Semantic modeling  procedures -- Logical data modeling -- Organisation modeling -- Technical integration of the MDM.
330   $aIn an increasingly digital economy, mastering the quality of data is an increasingly vital yet still, in most organizations, a considerable task. The necessity of better governance and reinforcement of international rules and regulatory or oversight structures (Sarbanes Oxley, Basel II, Solvency II, IAS-IFRS, etc.) imposes on enterprises the need for greater transparency and better traceability of their data. All the stakeholders in a company have a role to play and great benefit to derive from the overall goals here, but will invariably turn towards their IT department in search of the answ
410  0$aISTE
606   $aData protection
615  0$aData protection.
676   $a658.4/78
676   $a658.4038011
676   $a658.478
700   $aBonnet$b Pierre$0300555
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910829969403321
996   $aEnterprise data governance$92003183
997   $aUNINA