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Data Owners vs. Data Stewards vs. Data Custodians — The 3 Types of Data Masters and Why You Should Employ Them

Data governance is essential in today’s fast-paced, highly competitive organizational world. With the ability to acquire large volumes of heterogeneous internal and external data, companies require a discipline to maximize value, manage human risks and errors, and cut costs.

Data governance guarantees that data is consistent, trustworthy, and not misused. As companies face new data privacy regulations, it’s important to have data analytics in place. Data analytics can help businesses optimize their operations and make business decisions.

A data governance program that is designed well usually includes a governance team, a steering body that acts as the governing body, and a group of data stewards. They collaborate to develop data governance standards and policies, as well as implementation and enforcement methods that data stewards generally carry out.

Why is data governance important?

Data is undoubtedly an organization’s most valuable asset. Data governance ensures that data is usable, accessible, and secure. Effective data governance results in enhanced data analytics, which leads to better decision-making and operational support. It also helps to avoid data inaccuracies or discrepancies, which can lead to a variety of organizational challenges — including poor decision-making and integrity problems.

Data governance is also critical for regulatory compliance, ensuring that firms consistently meet all levels of regulatory obligations to avoid facing major financial issues. In fact, in 2021 JP Morgan was fined $125 million for violations in compliance control, mostly due to inadequate data and records keeping. In 2022, Morgan Stanley was fined a total of $60 million for data privacy violations that occurred between 2016 and 2019, resolving civil fines as well as a class action lawsuit over defunct data center equipment that had not been properly erased.

This is why a data governance strategy is more than just a plan. To implement a successful data governance program, significant roles and duties are required. This is essential for decreasing risks and operational expenses.

The three most important data governance roles

Data governance is a collaborative activity with roles that are distinct yet interconnected. The three most critical roles that any business must understand in the context of data governance are as follows:

Data owners

The data owner is in charge of the data in a certain data domain. A data owner must guarantee that the information inside that domain is correctly maintained across various platforms and business processes. Data owners are frequently represented on the executive committee as voting members or attending members with no voting powers. The following are their specific responsibilities:

  • Approving data glossaries and definitions
  • Ensuring the accuracy of information utilized inside and beyond the organization
  • Supervising operations that are directly relevant to data quality
  • Evaluating and approving the Master Data Management (MDM) strategy, outcomes, and actions
  • Working with other data owners to resolve data issues and misconceptions across business units
  • Second-level evaluation of data concerns highlighted by data stewards
  • Providing feedback to the higher-ups on software solutions, policy, or regulatory requirements that may affect the data owner’s data domain.

Senior staff is frequently assigned the job of the data owner. For example, the finance director may be the data owner of the organization’s financial data. However, due to this degree of seniority, a data owner is frequently unable to participate in activities aimed at controlling data quality on a daily basis. Because data ownership is frequently not a full-time profession, the data owner is usually assisted by one or more data stewards.

Data stewards

The primary distinction between a data owner and a data steward is that the data steward is in charge of managing the quality of the defined datasets on a daily basis. The data steward is the Subject Matter Expert (SME) who understands and explains the importance of the information and its use. The data steward also provides insight into the general purposes of the data to the data owner, but will be heavily involved in the intricacies of how these objectives might be realized. A data steward frequently works with other stewards within an organization through a data steward council.

This decision-making body weighs choices on potential data concerns and devises remedies. In most talks, the data steward represents the data owner. If the Data Steward Council cannot agree on how to fix a data problem, this individual will return to the data owner and/or the Steering Committee. Other responsibilities of the data steward include:

  • Creating data definitions and describing allowed values
  • Defining rules for data generation, data usage, or data derivatives
  • Recognizing and documenting current and desired data systems
  • And establishing data quality objectives

Some organizations have established official data steward roles, which are frequently filled by personnel within the business line who have been designated for such responsibilities. Other organizations provide data stewardship tasks to individuals who also have other duties. A successful data steward, regardless of how the role is defined, will adhere to the pre-established data definitions, detect data quality issues, and verify that the business adheres to the set standard.

Data custodians

A data custodian is responsible for developing and maintaining security safeguards for specific data collection in order to fulfill the Data Governance Framework standards established by the data owner.

Many individuals mix up data custodians with data owners. This is most likely due to the fact that data custodians are frequently the ones that physically or directly handle the storage and security of a data collection. However, simply because data is kept on a device that someone controls does not make them the data owner.

A data owner is a person who is generally in a senior company position, responsible for the categorization, protection, usage, and quality of one or more data sets. Data custodians are IT professionals who manage the security and storage infrastructure of one or more data sets according to an organization’s data governance policies. In small businesses where the same person may hold the responsibilities of the data owner and data steward, the data owner is likely to outsource day-to-day activities to data custodians directly.

Data masters: a must for data-driven organizations

Data governance adds meaning and security to an organization’s data by allowing teams to organize, record, and assess the quality of existing information assets. Data governance ensures that all colleagues have the context they need to trust data, access data, and produce important insights by defining terminology, setting policies, assigning duties, and more. Each of the mentioned roles is an essential component of a well-managed data governance organization. However, the organization’s MDM maturity determines who is the best fit for these jobs in an organization, and how these roles interact with one another.

Data alone does not solve issues or generate value; efficient data management and application do. Unsystematic methods of data management may easily transform data into a burden rather than a benefit for a business. Implementing a system with clear roles and responsibilities, such as data owners, stewards, and custodians is critical for effective data governance.

Data governance is more than just an option

Organizations now have massive volumes of data about their customers, clients, suppliers, patients, workers, and other stakeholders. An organization with solid data masters will be more successful, as the information will be used more correctly to understand the market and its target audience better. The same data governance will guarantee that your organization’s data is trustworthy, well-documented, easy to discover and access, safe, compliant, and confidential.

Data alone does not solve issues or generate value; efficient #datamanagement and application do. Unsystematic methods of data management may easily transform data into a burden rather than a benefit for a business. #respectdataClick to Post

Communication skills are essential for all of these professions, especially data masters. Every function must be able to articulate its own ideas, pain points, recognized risks and difficulties, business requirements, and ambitions. Of course, there will always be competing goals, as well as different interpretations of business terms, different applications of data, and so on, but that’s where data governance and masters come in. Make sure your business is well-positioned and well-governed to optimize data governance efforts while minimizing the risk of data breaches.