A data citizen is an employee who is given access to an organization's proprietary information. Use of the word "citizen" is meant to emphasize the idea that an employee's right to access corporate data also comes with responsibilities. While citizens in the United States have the right to assemble, for example, they also have a responsibility to obey federal, state and local laws. Similarly, an employee who has been granted the right to access corporate data also has a responsibility to support the company's data governance policies.
As corporate data citizens increasingly expect more transparent, accessible and trustworthy data from their employers, it has become more important than ever for the rights and responsibilities of both parties to be defined and enforced through policy. In some large organizations, data governance policies define and enforce the data citizen's right to easily access trustworthy data while data stewardship policies define and enforce the use of consistent data definitions and formats to ensure data quality.
Best practices for supporting data citizens include setting up a steering committee with high-level support for data governance, as well as embedding a network of data stewards within business lines. In large corporations, an additional central governance team may be necessary to coordinate governance and stewardship activities. In addition to enforcing the data citizen's right to easily access trustworthy data, governance controls ensure that data is used in a consistent manner across the enterprise. To support ongoing compliance with external government regulations, as well as internal data policies, audit procedures should also be included in the controls.
In the early days of computing, it took a specialist with a strong background in data science to mine structured data for information. Today, self-service business intelligence (BI) tools allow employees at every level of an organization to run ad hoc reports on the fly. Changes in how data can be analyzed and visualized allow workers who have no background in mathematics, statistics or programming be able to make data-driven decisions.