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Titlebook: Data Governance Success; Growing and Sustaini Rupa Mahanti Book 2021 The Editor(s) (if applicable) and The Author(s), under exclusive licen

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21#
發(fā)表于 2025-3-25 05:55:26 | 只看該作者
W. A. Knaus,D. P. Wagner,F. E. Harrellive of the industry sector, and data governance ensures that data is treated as an asset. This chapter discusses data governance as a key success factor and the various aspects of data governance success in a nutshell.
22#
發(fā)表于 2025-3-25 08:14:31 | 只看該作者
Book 2021sets throughout the enterprise by providing guidance in the form of policies, standards, processes and rules and defining roles and responsibilities outlining who will do what, with respect to data. While implementing data governance is not rocket science, it is not a simple exercise. There is a lot
23#
發(fā)表于 2025-3-25 13:16:06 | 只看該作者
24#
發(fā)表于 2025-3-25 18:58:33 | 只看該作者
Intervention and Control Groups tips and lessons learnt to help organizations to avoid some common failure traps and be successful in the implementation of data governance are also discussed in this chapter. Some of the key factors will be discussed in greater detail in the subsequent chapters.
25#
發(fā)表于 2025-3-25 22:21:43 | 只看該作者
Jose-Alberto Palma,Horacio Kaufmanne from, and track their data governance program. It is important to give a relevant and compelling view of the data to the top management and stakeholders to communicate the metrics and progress of data governance in an effective manner. Dashboards and scorecards have been discussed briefly in this chapter too.
26#
發(fā)表于 2025-3-26 01:36:26 | 只看該作者
27#
發(fā)表于 2025-3-26 07:07:57 | 只看該作者
,Data Governance—Metrics,e from, and track their data governance program. It is important to give a relevant and compelling view of the data to the top management and stakeholders to communicate the metrics and progress of data governance in an effective manner. Dashboards and scorecards have been discussed briefly in this chapter too.
28#
發(fā)表于 2025-3-26 11:45:41 | 只看該作者
29#
發(fā)表于 2025-3-26 16:32:42 | 只看該作者
Philippe Kachidian,Paolo Gubellini up the data governance maturity curve. In this chapter, the data governance models developed by Kalido, DataFlux, Informatica, Oracle, Microsoft, and IBM are discussed and compared. In addition, a new data governance maturity model consisting of ten dimensions is discussed in this chapter.
30#
發(fā)表于 2025-3-26 19:15:06 | 只看該作者
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