A data owner holds accountability for a specific dataset. At the end of the day, they are the person responsible for that data. That means they have the final say in who can access the data, as well as purview over security, classification, quality reporting, and other aspects of data management.
Technically, “data owner” is not itself a job title. Often, data owners are senior-level employees within specific departments or functional areas. However, they can also be subject-matter experts in mid-tier roles in some cases.
Below, we’ll look at data owners, including their key responsibilities, role within organizations, and how they compare to other data-related responsibility levels.
Data Owner Responsibilities
Just like it sounds, the data owner is all about ownership – and in this case, ownership is all about responsibility. The data owner is accountable for a particular dataset, and it’s their job to manage that data and the risk that comes with it.
Generally, data owners are the ones that have to ensure various definitions are in place. Ensuring data quality and taking action if issues are discovered also fall in their lane. Managing data quality reporting is another core responsibility.
Data owners are often required to ensure that all company policies and regulatory compliance needs are met. This can include the proper classification of data, ensuring correct management, guaranteeing appropriate levels of security, and establishing access control protocols.
However, data owners aren’t necessarily the ones that have to handle the more technical aspects that ensure their responsibilities are handled. Instead, they can coordinate with subject-matter experts, effectively directing tasks as necessary to comply with data governance policies or various requirements.
With such a high level of responsibility and accountability, companies often assign data ownership to senior-level employees. For example, the chief human resources officer may oversee personnel data, while financial data may fall in the hands of the head of the finance department.
In some cases, mid-level employees can also become data owners. This is more common with highly specialized data that is more niche and limited within the organization.
The Role of a Data Owner in Organizations
Data owners play a critical role in an organization’s operations. Someone has to bear the final responsibility for sensitive data; the data owner holds that accountability and oversees that data, reducing the risk of mishaps such as improper storage or faulty access controls.
Since having a single person oversee all of the data an organization collects is impractical – if not impossible – companies typically separate out the responsibilities based on functional areas. The goal is to select employees with the proper core knowledge, the right access to resources, and the personal motivation to ensure datasets are handled correctly and that all policy and regulatory compliance needs are met.
Within organizations, data owners serve as a point of accountability. It’s essentially a form of delegation, ensuring that department heads or similar upper-level employees take responsibility for data relating to their section’s operations.
Data owners then have the ability to delegate out tasks relating to the dataset, often by building a team that covers various data-related responsibility levels. This allows them to address personal knowledge or skill gaps relating to comprehensive data management, as they may not have subject-matter expertise in every core area.
When multiple functional areas all have needs relating to a specific dataset, it’s still common for there to be only one data owner. It allows organizations to centralize the management and oversight pertaining to that dataset.
However, in that scenario, organizations count on the data owner to collaborate and consult with any legitimate stakeholders within the company. This allows them to work together to establish or alter workflows, infrastructure, access, and other factors that impact multiple functional areas. But it also ensures that data quality and other broad-scope responsibilities are generally in a single person’s hands, reducing organizational complexity.
Data Governance: Data Owners, Stewards, and Custodians
Data governance includes processes for ensuring the usability, integrity, availability, and security of data within organizational systems. Often, the core goal of data governance is to prevent misuse and unauthorized access while ensuring accuracy, consistency, and trustworthiness in regard to data.
In the world of data governance, there are three primary responsibility levels. Along with the data owner, there can be data stewards and data custodians. Each of these roles has different degrees of access and duties relating to the dataset in question.
Data Owner vs. Data Steward
As mentioned above, data owners have full responsibility and accountability in regard to a dataset. However, since senior-level employees are more commonly selected for this role, there are challenges to navigate. For example, data owners may be short on time or lack specific subject-matter expertise that will play a crucial role in proper data management or compliance.
Fortunately, the difficulties are typically covered by another data responsibility level: the data steward. Data stewards function as the subject-matter expert, allowing them to offer guidance and provide assistance to data owners regarding data governance, policy adherence, and regulatory compliance.
A data steward usually needs a deep understanding of how a dataset is stored, protected, and documented, though not necessarily in a technical sense. Some focus more on operational areas, individual projects, or similar niches.
In many cases, data owners appoint data stewards, not unlike choosing an employee for a project team. As a result, data owners are essentially the bosses over a dataset, giving them the ability to delegate tasks and secure expertise as required.
Additionally, data owners may assign multiple data stewards to one dataset. For instance, they may select an operational data steward for their functional understanding of a business area and a technical data steward to assist with the technology-related aspects of data management and storage.
Data Owner vs. Data Custodian
While data owners have the ability to manage data directly, the lack of available time or subject-matter expertise can make them ill-suited for those tasks. As a result, organizations may add data custodians to the mix to ensure those responsibilities are covered.
Like data stewards, data owners can typically select data custodians to ensure the best employee for the job is handling the related duties. Once chosen, data custodians primarily mainly manage the more “physical” aspects of data management, managing storage and security.
In many cases, data custodians have technical expertise. As a result, they may work primarily in an IT role, allowing them to secure infrastructure, create needed storage mechanisms for data organization, ensure backups occur at the proper times, and otherwise meet the technical needs of any data governance policies.
Essentially, data custodians fill any technical gaps that may prevent the data owner from directly handling various dataset responsibilities. Again, it isn’t unlike the data owner bringing a member onto a dataset project team, giving them access to critical expertise while maintaining full accountability.