When a major data incident occurs, people at the top want answers. Was the IT team’s network security at fault? Was it the product team’s lax data collection? Or are the legal department’s inadequate compliance guidelines to blame?
No one can say—and that touches on a common organizational pain point: who’s in charge of data accountability?
Every modern organization aims to be data-driven. Yet when critical data assets lack clear stewardship, decisions stall, quality suffers, and the finger-pointing begins. Who decides what data is correct? Who is responsible for fixing it when it’s not? Who allowed sensitive data to be shared without proper authorization? When there’s no one to answer those questions, data can become a liability rather than a strength. And leadership wants to know how it got this far without anyone noticing.
Robust data governance policies build a clear, accountable framework for information assets. They address the ambiguities and foster collaboration within the data owner vs. data steward vs. data custodian dynamic, transforming data from a source of frustration into a powerful driver of organizational success.
Data Owner vs. Data Custodian – What’s the Difference?
The chief difference between an owner and custodian of data is their focus:
Data owners are individuals or departments responsible for a specific data asset or domain. They oversee its strategic alignment, quality, integrity, and compliance throughout its entire lifecycle. They’re also the authoritative voice on the data’s business context and requirements and are held accountable during data-related audits. Most data owners are from the business teams that create or use the data, meaning they have deep expertise in it.
A data owner’s primary responsibilities include:
- Defining why specific data is collected, how it will be used, and what its business purpose is. This aligns data initiatives with broader organizational goals.
- Establishing clear and consistent data element definitions, setting business rules, and determining acceptable data quality standards, such as what constitutes accurate, complete, or consistent data.
- Assigning sensitivity levels to data and assessing its use, storage, and potential exposure risks.
- Approving who can access specific datasets and for what purposes.
- Ensuring the data’s collection, use, storage, and retention policies are in line with relevant privacy laws like GDPR, HIPAA, and CCPA) as well as internal corporate policies.
- Setting policies for how long data is retained, when it’s archived, and how it’s securely disposed of.
Data custodians are individuals or teams responsible for data’s technical stewardship and management. Typically part of the IT team, operations, or dedicated data management team, they ensure data is securely stored, readily accessible, and managed according to the data owner’s specifications.
A data custodian’s chief responsibilities are:
- Providing, managing, and optimizing the databases, data warehouses, data lakes, and cloud storage solutions where data resides.
- Implementing and maintaining technical controls like encryption, access controls, and intrusion detection systems that are used to protect data based on the data owner’s classifications
- Setting up and executing backup strategies and disaster recovery plans.
- Designing, building, and maintaining data pipelines to ensure data flows efficiently and accurately between various systems.
- Monitoring database and system performance and performing routine maintenance, including patching and upgrades.
- Implementing automated validation rules, monitoring mechanisms, and data cleansing scripts to enforce quality standards the data owner sets.
- Collaborating with data owners and other stakeholders to devise technical responses to data breaches or misuse.
A real-world example illustrating the difference between data owners and custodians is a large healthcare system managing patient medical records.
The Health Information Management (HIM) Department might act as the data owner for patient medical records, defining what data is collected (diagnoses, treatments, visit notes), ensuring patient care and billing accuracy, and determining how long records must be retained to meet various requirements. The Healthcare IT Department would be the data custodian, maintaining electronic health records (EHR), securing patient data, performing system backups, implementing access controls, and ensuring system reliability.
This owner/custodian partnership is critical to ensuring data is usable and protected across its lifecycle. The data owner sets data’s “what” and “why” strategies while the data custodian manages the technical “how” and “where” to bring those requirements to life.
Where Does the Data Steward Fit In?
Data owners chart data’s strategic course, and data custodians protect its technical infrastructure. Data stewards are vital operational experts who ensure data policies are applied practically and that data remains healthy and usable in its various domains.
Data stewards are usually embedded in business units. These subject matter experts have a deep understanding of how data is used day-to-day and form a crucial link between a data owner’s strategic directives and a data custodian’s technical implementations. They focus on data’s daily management, often working directly with data users. They also provide essential feedback to data owners and custodians and are the ones who translate high-level data policies into actionable, everyday practices.
Areas of expertise include:
- Developing and maintaining in-depth business definitions for data elements within their domain so that everyone understands the data the same way.
- Monitoring data quality for accuracy, completeness, and consistency within their specific datasets. They identify errors, inconsistencies, and gaps and work with data entry personnel, owners, and custodians to resolve root causes.
- Ensuring adherence to data governance policies, standards, and procedures.
- Maintaining and enriching data catalog metadata, including data lineage, usage context, and ownership information.
- Providing support and training to users on proper data usage and regulatory compliance. They are often the first point of contact for business colleagues with data-related questions.
- Identifying significant data quality issues, security concerns, or policy non-compliance and escalating them to the appropriate data owner or custodian for resolution.
- Assisting authorized users in their business unit with data access requests. They frequently coordinate with data custodians to ensure appropriate permissions are granted.
To see the data steward’s role in action, picture a global eCommerce company’s product information domain.
The data owner might be the Head of Merchandising, defining which product attributes (size, material, pricing) are essential, how product descriptions are structured, and image quality standards, ensuring consistent product presentation across sales channels. The data custodian would be the IT team managing the product information management (PIM) system and inventory databases. They make sure the system is secure, scalable, and integrates smoothly with the eCommerce platform.
In this scenario, the data steward might be the Product Category Manager responsible for ensuring product descriptions are accurate, images are correctly linked, pricing is consistent, and inventory counts are reliable. They identify errors in product listings, work with vendors to get complete data, and train sales associates on how to find and use product information.
Why Clear Roles Matter in Data Governance
Without well-defined roles for data owners, custodians, and stewards, organizations can lose trust in their data, see operational costs increase, and face significant regulatory risks.
Precise data governance roles establish clear accountability, prevent confusion, and enable swift action when issues arise. It improves data quality and reliability as data owners set standards, data custodians implement technical controls, and data stewards monitor data health. This structured approach also strengthens security and compliance, minimizing vulnerabilities to sensitive information. When roles are well-defined, resource allocation is optimized, duplicated efforts are avoided, and data-driven decision-making is accelerated. Specified roles ensure data is trusted and accessible, foster a culture of data accountability, and promote better organizational practices.
There can be significant consequences when roles are ambiguous or overlapping. For instance, a fast-growing tech company without formal data owners for product usage data could end up with conflicting definitions and poor data quality from various engineering teams (the de facto custodians). This can result in stalled product launches, analytics confidence erosion, and time wasted on reconciling data.
Establishing solid data governance roles transforms data from a potential liability into a strategic asset, building resilient, efficient, and data-driven organizations where everyone knows their part in guarding and leveraging data resources.
Key Takeaways for Choosing the Right Data Governance Roles
Your organization’s data governance framework should be tailored to its unique needs, culture, and data maturity. The data governance tool that works for someone else might not be the right one for you. Consider these factors when establishing and optimizing your data governance roles:
- Start strategically, grow incrementally. Instead of rolling out an enterprise-wide framework from the get-go, first identify your most critical data domains or the areas facing the biggest data challenges. Then define the data owner, custodian, and steward for these top areas. Once you can demonstrate tangible successes, continually expand the framework.
- Leverage the existing organizational structure. While acknowledging new responsibilities might emerge, align data governance roles with your existing organizational framework. Department heads are often natural data owners, and IT teams are well-suited for data custodian roles. Business analysts can be excellent data stewards.
- Create clear documentation to formalize roles. Each role’s description should outline its specific responsibilities, accountabilities, decision-making authority, and key performance indicators (KPIs).
- Promote collaboration and communication. Establish regular forums, working groups, and clear communication channels to discuss data quality issues, policy updates, security concerns, and strategic data initiatives. Data catalogs facilitate shared understanding and can be incredibly valuable here.
- Provide training and continuous support. Provide targeted training tailored to each role’s responsibilities, i.e., data strategy and risk management for data owners, metadata principles for data stewards, and evolving security best practices for data custodians.
For long-term success, get top leadership’s backing to make data governance an organizational priority. Beyond that, define clear metrics to measure effectiveness, adapt roles, and continuously align efforts with evolving organizational goals.
Establishing robust data governance is a strategic investment in your organization’s future. AI-powered Velotix helps organizations transform data from a collection of bits and bytes into well-managed, trusted, and strategic assets. With intelligent automation and policy enforcement, it streamlines governance at scale, saving time, reducing risk, and accelerating data value.
Book a demo today to learn more.
