The key principles of a data governance strategy
Petrus Keyter, Data Governance Consultant at PBT Group
With just 3% of data in a company meeting quality standards, data governance has become more important than ever. This is even more so the case given how businesses in South Africa and the rest of the world are adopting a data-driven approach in their efforts to embrace a focused customer-centric model. Data, along with the people inside an organisation, have become an organisation’s most high-valued assets.
Data governance must be in place to ensure data is used to its full potential inside the organisation. Everything from what to eat and what entertainment to be had, to what suggestions to make regarding products or services based on a customer’s historic interactions with a company’s app, is based on data. And hopefully, all that data is trusted and has been ethically obtained. Take a banking app as an example. A customer opens an account, deposits their salary into it, and uses it to pay their bills. In the background, the bank will use some form of AI analysis behavioural patterns to suggest to the customer what services and products they can benefit from.
Data governance has become a key trend and priority for 2024 due to how companies are leveraging it to access trusted data for their daily operations. Throughout this, AI’s impact on data cannot be ignored. If this advanced technology is used well, it can help create high-quality, trusted data.
Core data governance principles
In the past, the thinking was that data governance belonged to the IT department because it was run by IT people. Businesses never got involved resulting in data governance not receiving top-down support. Fortunately, this has changed. Now, companies have become accustomed to using data. The decision-makers realise the importance of being involved in data governance due to regulatory requirements.
As part of this change in approach, I believe that there are seven key principles to keep in mind when it comes to data governance:
- Establish accountability: Clearly defined roles and responsibilities are crucial for effective data governance. This includes assigning data owners, data stewards, and data custodians who are accountable for various aspects of data management and ensuring compliance with governance policies. These should be guided and supported by a knowledgeable data governance team. After all, if nobody takes accountability for data governance, then nobody will drive it effectively inside the organisation.
2. Foster data stewardship: Data stewards (the data foot soldiers in the business) play a key role in managing the organisation’s data assets. They ensure data transparency and manage and resolve data quality issues. Data stewards therefore ensure data is always of the highest quality and fit for purpose. They act as a bridge between IT and the business, making sure that the data serves the organisational needs and supports the data strategy and business strategy. These data stewards execute data governance, manage metadata, and look at data quality issues, amongst others.
3. Build data transparency: This is what data governance is about – understanding the data sources and what they are. Therefore, clear documentation must be put in place regarding data sources, data classification, data lineage, business data quality rules, and the processes used for data management. This documentation must be maintained and socialised with all employees at the company. Doing so creates a transparent environment that helps build trust in the data and holds the company accountable for how the data is used.
4. Ensure integrity and quality of the data: If a company does not have high-quality data, then none of the business decisions made with that data will be useful. Ensuring data accuracy, consistency, and reliability is therefore fundamental. This involves implementing processes that maintain data quality throughout its lifecycle — from collection and storage to analysis and reporting. It also involves the effective remediation of any data issues encountered.
The above four points are fundamental to any data governance strategy. Equally important, are the next three which underpin much of the focus areas of what has been discussed:
5. Data security: Protecting data from unauthorised access, usage, and data breaches is critical. This involves implementing appropriate security measures, such as encryption, access controls, and regular audits of data access and usage.
6. Compliance with regulations: Adhering to relevant laws, regulations, and standards is essential. These include but are not limited to national laws (POPI Act), international laws (GDPR or CCPA) or industry-related laws (for instance, financial, mining, telecommunications, and so on). All this requires the company to keep abreast of the regulatory landscape and adjust its governance practices accordingly to ensure compliance.
7. Data ethics: Data governance should promote ethical data management practices, ensuring that data is used in a way that respects customer privacy and other societal norms. In the case of the medical industry for example, not disclosing patient information for all to see.
Establishing these seven principles within an organisation provides a solid base for effective data governance practices.
Join me next time as I focus on the topic of minimum viable product (MVP) in data governance.
