Data governance

From Wikipedia, the free encyclopedia

Data governance encompasses the people, processes and technology required to create a consistent, enterprise view of an organisation's data in order to:

• Increase consistency & confidence in decision making
• Decrease the risk of regulatory fines
• Improve data security
• Consistent information quality across the organization
• Maximize the income generation potential of data
• Designate accountability for information quality

Data Governance initiatives improve data quality by assigning a team responsible solely for data's accuracy, accessibility, consistency, and completeness, among other metrics. This team usually consists of executive leadership, project management, line-of-business managers, and data stewards. The team usually employs some form of methodology for tracking and improving enterprise data, such as six sigma, and tools for data mapping, profiling, cleansing and monitoring data.

Data governance initiatives may be inspired by the desire to comply with the law (compliance), the desire to improve visibility to customers and the supply chain worldwide, connecting information after rapid company growth or corporate mergers, or simply the desire to use enterprise data to improve knowledge-worker efficiency. Many data governance initiatives are also inspired by past attempts to fix information quality at the departmental level, leading to incongruent and redundant data quality processes. Most large companies have many applications and databases that can't easily share information. Therefore, knowledge-workers within large organizations often don't have access to the information they need to best do their jobs. When they do have the data, the data quality may be lacking. By setting up a data governance practice or Corporate Data Authority, these problems can be mitigated.