Providing guidance to ensure that data is accurate, consistent, available and secure is the focal point of data governance.
Optimal data governance is achieved through the enterprise-wide communication of a compelling vision for change, setting achievable performance targets and allocating appropriate enterprise resources. The vision is supported by the senior management and business sponsors of the data governance initiatives.
A successful data governance approach integrates the processes, people and technology needed to manage data effectively and efficiently. It begins with an enterprise-specific model consisting of defined roles and responsibilities. Adhering to the complexities of enterprise business rules, policies and standards is an essential role of data owners and includes maintaining and applying these standards as data is created. While data stewards do not own the data, they are the caretakers and are accountable for the management of data assets by ensuring data is understood, used and shared effectively. Data owners and data stewards must be provided with the knowledge, training, tools, forums and processes to be effective in their jobs.
To manage data assets, enterprises need to establish both high-level and detailed rules and procedures. These data policies might include the adherence of data to business rules, enforcing authentication and access rights to data, complying with laws and regulations, and protecting data assets.
The precise criteria, specifications and rules for the definition, creation, storage and usage of data within an organization are referred to as data standards. These range from basic items like naming conventions, number of characters and value ranges to more complex standards such as quality measures, retention rules and backup frequency.