Data governance

Definition:

Data governance is a process to ensure data meets precise standards and business rules as it is entered into a system. Data governance enables businesses to exert control over the management of data assets. This process encompasses the people, process, and technology that is required to ensure that data is fit for its intended purpose.

Data governance is important for different types of organizations and industries, especially those that have regulatory compliance such as finance and insurance. To achieve compliance, organizations are required to have formal data management processes in place to govern their data throughout its lifecycle.

Implementing a data governance strategy:

It is important to consider the people, processes and technologies that must go into a holistic approach to data governance.

1. People

   The first step in implementing a data governance program is to build a team and define who in your organization will be responsible for the data assets. These data owners will be accountable for the quality of the data and the support of data quality activities and initiatives company-wide.

   The data team must ensure that the data governance initiatives are aligned with business needs and that the data meets their requirements. Data governance sounds like something that should be aligned with the IT portion of your organization, but in reality it should be closely aligned with the business to ensure stakeholders can easily access the information they need to make data-driven business decisions. Without this critical communication, your organization will end up with a big data strategy as opposed to a data governance strategy.

2. Process

   Next, data processes must be developed. These include definitions of how data will be stored, moved, changed, accessed and secured. Control, audit, and monitoring processes must also be put in place, especially for compliance reasons in highly regulated industries.

   Focusing your data governance processes on the business and its needs is very important, and the processes must reflect that.

3. Technology

   Data governance cannot be completed with technology alone, but organizations should leverage solutions that will help with your governance initiatives.  Examples include technology that will help enforce business rules, monitoring and reporting software, and data quality solutions.

Learn more about data quality and its critical role in the implementation of your data governance strategy.

Learn more about how our data management solution can help with your data governance initiatives.

Learn more about the relationship between data quality and data governance.

Learn more about data quality management.

Learn why your organization needs data governance.