Building an effective data governance framework

Editor's note

Effective data governance serves an important function within the enterprise, setting the parameters for data management and usage, creating processes for resolving data issues and enabling business users to make decisions based on high-quality data and well-managed information assets. But implementing a data governance framework isn't easy. Complicating factors often come into play, such as data ownership questions, data inconsistencies across different departments and the expanding collection and use of big data in companies.

Data stewardship adds another dimension -- and more challenges -- to data governance efforts. Whether an organization hires full-time data stewards or delegates stewardship responsibilities to existing employees, business units sometimes are reluctant to accept the new arrangement for maintaining data definitions and enforcing polices on data use. In an ideal environment, all users adopt a stewardship-minded approach and take responsibility for handling data in a way that both meets their immediate business needs and serves the company's overall requirements for data quality and consistency. But data stewardship processes need to be attuned to an organization's corporate culture in order to help foster internal adoption and compliance.

Developing a successful data governance strategy requires careful planning, the right people and appropriate tools and technologies. This essential guide offers best-practices advice for managing data governance projects, an exploration of data stewardship and details about common problems that organizations have experienced while instituting data governance programs -- and how they solved them.