Who really owns your data?
Andreas Bartsch, Head of Innovation and Services at PBT Group
Data has long been seen as a strategic asset. But in today’s AI-driven world, its real value comes down to something far more practical: responsibility. So, when data quality falters or compliance gaps appear, who is actually accountable?
Many organisations are still figuring this out. AI is certainly raising the stakes, meaning that vague job titles and blurred lines of responsibility will not cut it any longer.
In our work with data-led teams, we have found that the strongest data cultures share a common trait: clear, well-defined roles. Specifically, three roles tend to anchor a successful, governed, and insight-ready environment: the Data Owner, the Data Product Owner, and the Data Governance Owner.
The Data Owner: Accountability at the source
The Data Owner sits within the business and understands exactly what the data represents, whether that is customers, transactions, or operational metrics. Their job is to ensure that the data in their domain is accurate, properly classified, and securely accessed.
They are the ones defining usage policies, retention rules, and quality benchmarks. In short, they carry the ultimate accountability. If something goes wrong, it is the Data Owner who must answer for it.
Typical job titles? Think Head of Credit Risk, Finance Reporting Lead, or Operations Manager. These are business leaders with skin in the game.
The Data Product Owner: Turning data into value
Where the Data Owner focuses on what the data is, the Data Product Owner focuses on what it does. They are responsible for delivering useful outputs that meet real business needs.
This role bridges the gap between data teams and end users. They manage backlogs, align technical work to business priorities, and ensure that the final product is both usable and valuable.
You will often find Data Product Owners in Business Intelligence (BI) teams, digital transformation squads, or embedded within analytics functions. Their job is to make sure data products actually solve problems.
The Data Governance Owner: Holding the structure together
Every system needs rules. That is where the Data Governance Owner comes in. Their role is to define and maintain governance frameworks to ensure consistency, compliance, and alignment across departments.
This includes everything from data classification policies to regulatory mandates like POPIA or GDPR. They are often tasked with building data literacy, driving stewardship initiatives, and coordinating with multiple stakeholders to enforce enterprise-wide standards.
These are your Chief Data Officers, Compliance Leads, or Data Governance Managers.
So, who owns data quality?
It is tempting to think data quality belongs to one team. In reality, it is shared. However, accountability starts with the Data Owner.
Daily quality efforts are usually carried out by Data Stewards, who work hand-in-hand with the business to clean, maintain, and document data. Data Engineers enforce quality rules through pipelines and systems. Product Owners ensure that data outputs are fit for purpose. And business users play an underrated role: flagging issues early when something looks off.
The need for clarity trumps all
Not every organisation uses the same job titles. What one calls a Product Owner, another may call a Data Platform Lead. That is okay. What matters is that everyone understands their role and works together towards the same goal: trustworthy, usable, and compliant data.
Without clarity, data becomes a liability. With it, it becomes an engine for growth. And in a world where AI is only as good as the data it is trained on, that clarity is more important than ever.
