26 July 2022 (Updated: 28 July 2022) - 2 MINS READ
What do we mean when we claim the data is secure? It means:
- Data is only accessible to authorized users in authorized ways.
- Data is auditable, which means that all accesses, including modifications, are logged.
- Data complies with all regulations.
The goal of data governance is to increase trust in data. Trustworthy data is required to enable decision making and risk assessment.
No matter how large the organization is or the volume of data, the principles of data governance remain the same. However, data governance practitioners make decisions about tools and ways to implement them based on practical factors that are affected by the environment in which they work.
It is important to note that data governance is not just about data security; it is more than that. Data must be trustworthy, and data quality and integrity are equally crucial.
Enhancing trust in data
As noted before, the ultimate goal of data governance is to establish trust in data. To ensure data trust, a data governance strategy must address three key aspects:
Data governance is a collection of processes, roles, policies, and standards that ensure data is secure, accurate, and available across the organisation. In other words, it is the process of defining security guidelines and policies and making sure they are followed by having authority and control over how data assets are managed. It defines who can take what actions based on what data, in what circumstances, and with what methods.
The practice of data governance also includes adhering to external standards set by industry associations, government agencies, and other stakeholders. Regulations such as the GDPR and many others impose legal accountability and severe penalties on firms that fail to adhere to governance principles around data privacy, retention, and portability.
Why is data governance important?
Data governance is not only about managing the rules but also making data useful. Effective data governance implementation ensures that high-quality data must be efficiently available to the right people throughout the organisation.
Data governance vs. data management
- Data governance describes the general structure that need to be in place.
- It has policies, procedures, and accountability.
- It’s more about what should happen and how things should happen.
- The goal of data management is to put all of the policies into practice.
- It’s a hands-on daily effort to make sure that the policies we put in place are being followed.
The first thing we need to consider when it comes to data governance is who is engaged and what their roles are. There are usually several roles, but the most important one is data owner or data sponsor. These are the individuals who have ultimate decision-making authority over the data and are solely responsible for ensuring that the data is accurate and up to date. These individuals have a deeper understanding of the groundwork that’s being done with the data. There could be many data owners or data sponsors. For instance, a sales data owner, an inventory data owner, etc.