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An enterprise data strategy defines the approach an organization will take to manage and use its data to achieve its business and technology goals and to realize a competitive advantage.
Benefits of a data strategy include, but are not limited to:
- discovering data's value to the organization and to each business unit;
- outlining the enterprise approach to data management by domain and prioritizing its implementation;
- identifying the organization's strategic priorities for data management;
- developing a high-level roadmap for data management component projects; and
- detecting the organization's current data management challenges by domain.
It is important to base an enterprise data strategy on an industry-standard information management framework. Doing so ensures that the organization's data strategy includes all the aspects of enterprise data management and that all the components are examined equally.
Many organizations focus their data management efforts on only one or two aspects, such as data governance and analytics, neglecting the other extremely important components. Without including all the domains of enterprise data management in the enterprise data strategy, an organization runs the risk of overlooking the ways some aspects influence and are influenced by others -- e.g., how metadata management is essential to data governance success, how data architecture is crucial to analytics capabilities, etc.
Data strategies are focused on the present and near future, with a usual view of two to three years as the limit. Plans that are derived from the data strategy should be focused to achieve results before the strategy's revision.
A data governance program is one possible result of an enterprise data strategy. A data governance program describes how an organization will develop and implement the policies, practices, standards and procedures that manage data and information based on the organization's vision and mission as stated in the data strategy.
The data governance program should be aligned with other components of data management -- e.g., metadata management, data quality, master data, etc. -- and this alignment should be addressed as part of the data strategy.
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