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Learning from Others: Best Practices for Data Governance

Date: September 25, 2008

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Knowing where you are makes all the difference when trying to determine the optimal path forward. Increasingly, savvy organizations are realizing they need a model to assess their information initiatives, especially for data governance programs. At its root, data governance is a quality control discipline for managing, using, improving and protecting organizational information. Effective data governance can enhance the availability and integrity of a company’s data by fostering cross-organizational collaboration and structured policy-making.

Tune into this DM Review Web Seminar with IBM's Patrick Connolly, Product Marketing Lead for IBM’s InfoSphere marketing and strategy team, to learn how your organization can employ a data governance maturity model to better understand and manage your information environment.

Attendees will learn:

- The 11 stages of data governance maturity
- to determine where you are on the curve
- How your organization stacks up against other companies
- Why a maturity model is critical for managing data governance
- How to balance departmental needs with enterprise objectives

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