Data governance supports data protection — in particular, the General Data Protection Regulation (GDPR)
Just a few years ago, the discipline of data protection was mainly about securing who had access to your data and ensuring the data did not fall into the wrong hands. Data governance, on the other hand, was mainly about managing your data and improving your data quality.
Despite what many people think, data governance and data protection have never been the same thing, and the line between the two disciplines used to be very clear.
But now we have a relationship between data governance and data protection, where they work together and complement each other. What happened?
The General Data Protection Regulation (GDPR) happened. The European Union personal data regulation has raised the data protection bar and required businesses to better manage, store and document any personal data they may hold on European citizens.
The GDPR requirements are creating the overlap between the two disciplines.
In order to understand how, we need to start by defining what data governance is. Expert in data governance, Nicola Askham, defines it as:
“Proactively managing your data to support your business achieving its strategy and vision.”
Data governance is achieved by implementing a data governance framework that consists of policies and processes, as well as roles and responsibilities. How does that work together with data protection? Well, let’s apply it to some of the data protection requirements listed in the GDPR.
3 data protection requirements listed in the GDPR
1. Accountability
According to the GDPR, companies that manage personal data on a larger scale are obligated to have someone accountable, a data protection officer (DPO) or chief data officer (CDO), whose main task is to make sure the GDPR is met and that individuals have a point of contact if they have questions or concerns about their personal data.
In a data governance setup, on the other hand, you may have a data governance team with multiple data owners and data stewards, who are all responsible for managing the organization’s data governance.
Obviously, you’ll have the greatest business impact if you enable all of these employees to work side by side, complimenting and supporting each other, instead of laying the full data responsibility on one person, like the DPO or CDO.
2. Location
According to the GDPR, businesses need to be able to identify where they store personal data. Ideally, your organization would have a comprehensive data map or data inventory overview.
But, if you already had robust data governance in place prior to the GDPR, you may already have a data catalog that tells you what data belongs to which systems, and data lineage diagrams that show you how data is flowing through the organization.
3. Accuracy
According to the GDPR, personal data shall be accurate and, where necessary, kept up to date, which raises the demand for a certain level of organizational data quality.
After all, how will you protect the data if you cannot even guarantee its quality? If you want to improve the quality of your data, having a data quality issue management process and data quality reporting — all basic parts of a solid data governance initiative — should hopefully help resolve it.
A long-lasting data governance approach goes beyond data protection
As you see, data governance supports data protection, and in particular the GDPR, in numerous ways. Having a solid data governance framework will help your organization to continue meeting GDPR requirements in a sustainable manner. So, if you do not already have the level of data governance you could wish for, or if your data governance efforts do not encompass all your personal data, there’s no better time than now to give it a boost.
GDPR is not going to go away. Now, organizations need to go from project mode into business as usual with the GDPR, and that’s where long-lasting data governance efforts pay off. Furthermore, data governance does not only support data protection, but is the key driver for many positive business outcomes, such as efficiency, accurate reporting, regulatory compliance support, reputation and customer experience improvements.
Additional benefits of an effective data governance strategy
Effective data governance provides numerous benefits that extend beyond mere compliance and data protection. Here are some of the key advantages:
- Enhanced data management: The right governance strategy ensures that data assets are managed properly throughout their lifecycle. This includes data classification, metadata management, and establishing robust access controls to prevent unauthorized access to sensitive data. Proper management of data assets improves overall data security and usability.
- Automated workflows and streamlined processes: If your strategy is truly comprehensive, it can integrate various data governance tools to streamline and automate your workflows. Automation reduces manual effort, minimizes errors, and enhances efficiency across the organization.
- Improved data security: With effective data governance, organizations can implement strong security measures to protect against data breaches and data loss. This involves regular audits, data integrity checks, and maintaining data privacy. Robust security measures help safeguard sensitive information and maintain customer trust.
- Data-driven decisions: A strong data governance program means you get access to high-quality data that can be trusted. With that level of data, your decision-making can truly become driven by data. Organizations can leverage big data and machine learning to gain insights and make better business decisions.
- Increased efficiency and productivity: Streamlined data management processes lead to increased operational efficiency and productivity. By eliminating data silos and ensuring data quality, organizations can reduce redundancy and improve collaboration across the board.
Effective data governance supports not only data protection and regulatory compliance but also drives numerous positive business outcomes, making it a critical component of any successful data strategy.
Learn more about how to develop a data governance operating model for your organization:
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