Defining Data Governance Roles and Responsibilities

Who is responsible for data governance? The short answer — anyone and everyone who consumes data within the organization.

To be clear, that does not mean that you need an over-engineered data governance program — it simply means you need to have clear and defined data governance roles and responsibilities within your organization that everyone can understand.

Additionally, as with any data initiative — the data governance roles your organization needs are unique to you. The extent and intricacy of data governance you require hinges on your specific operational dynamics, the nature of your business, and the kind of data you handle. So, the roles and responsibilities within your data governance initiative will vary based on these factors and can range from a few pivotal roles to a more extensive team.

In this blog, we cover:

1. 1. The key roles and responsibilities for data governance ↵
   2. How to assign responsibilities for an effective data governance team ↵
   3. Training and development for new roles ↵

What are the Key Roles and Responsibilities for Data Governance?

In a successful data governance program, specific individuals take on vital roles, each with their own set of responsibilities. Clearly defining these roles is crucial to building a strong foundation for your data governance initiative. The team includes people in baseline roles (those who provide necessary leadership and support), and those in specialized roles (who handle daily data governance tasks).

Clear data governance roles prevent overlap, confusion, and costly delays across your org.

Baseline roles and responsibilities for data governance include: 

• Data Governance Sponsor: This role is typically filled by a C-suite level executive, such as a Chief Data Officer (CDO) or Chief Information Officer (CIO). Their main responsibility is to champion and advocate for the data governance initiative at the highest level of the organization. They provide the necessary support, resources, and authority to ensure the success of the program. The Data Governance Sponsor is usually business-focused but may also have technical knowledge.
• Data Governance Leader: This role is responsible for steering the overall data governance program to success. They provide leadership, strategic direction, and guidance for the initiative. The Data Governance Leader ensures that the program aligns with the organizational goals and objectives, and they coordinate and collaborate with various stakeholders to drive the implementation of data governance practices. This role is typically business-focused but may also require a good understanding of technical aspects.
• Data Owners: These individuals are responsible for the management and oversight of specific data domains or data sets within the organization. They have accountability for the quality, integrity, and availability of the data within their domain. Data Owners define data policies, standards, and procedures, and they work closely with Data Stewards to ensure compliance and adherence to these guidelines. Data Owners are usually business-focused, as they have a deep understanding of the data and its business context.
• Data Stewards: These individuals are responsible for executing the day-to-day data governance activities. They ensure that data is properly classified, documented, and protected according to the defined policies and standards. Data Stewards work closely with Data Owners, Data Users, and other stakeholders to resolve data issues, address data quality problems, and support data-related initiatives. Data Stewards need to have a good understanding of both business and technical aspects to effectively carry out their responsibilities.

While the baseline roles may have a primary focus on either the business or technical aspects, successful data governance implementation requires collaboration and coordination between both domains.

Specialized roles and responsibilities for data governance include:

• Data Admins: These folks are responsible for ensuring the accessibility and reliability of data systems. They manage and maintain the technical infrastructure, databases, and data management tools. Data Admins focus on data system administration, data integration, data storage, backup, recovery, and data system performance. Their role is primarily technical, ensuring that the data systems are functioning optimally and meeting the organization’s data governance requirements.
• Data Custodians: These individuals are entrusted with the safe storage, transfer, and enforcement of data security. They are responsible for implementing and enforcing data security controls, managing data access rights, and ensuring compliance with data privacy regulations. Data Custodians focus on data protection, data encryption, data access controls, data incident response, and data privacy. Their role is both technical and business-focused, as they need to balance data security requirements with operational needs.
• Data Users: These individuals leverage data to meet organizational goals while adhering to governance policies. They include business analysts, decision-makers, data scientists, and other stakeholders who rely on data for their work. Data Users focus on using data effectively, analyzing and interpreting data, making data-driven decisions, and following data governance policies and guidelines. Their role is primarily business-focused, as they utilize data to drive business insights and outcomes.
• Regulatory Compliance Officer/Expert: This role is critical, especially in regulated industries. Regulatory Compliance Officers or Experts are responsible for maintaining the alignment of data governance strategies with legal and industrial stipulations. They ensure that the organization’s data governance practices adhere to relevant regulations, industry standards, and internal policies. Regulatory Compliance Officers monitor and assess compliance risks, develop compliance frameworks, facilitate necessary compliance audits, and provide guidance on data governance practices. This role is primarily business-focused, with a deep understanding of regulatory requirements and their implications for data governance.
• AI Governance Oversight Admin: As you expand your use of AI and machine learning, this role takes ownership of how those systems align with your governance policies. That includes assigning responsibility for the data feeding your models, tracking AI outputs, and ensuring compliance with ethical and regulatory standards. You can embed these responsibilities into existing roles like Data Owners or assign them to a Center of Excellence. As your AI efforts grow, consider formalizing this into a dedicated role to maintain clear accountability.

These specialized roles work in conjunction with the baseline roles to ensure comprehensive data governance coverage across technical, operational, and compliance aspects.

How to Assign Responsibilities for an Effective Data Governance Team

Building a high-functioning data governance team requires a thoughtful assignment of responsibilities, which should be tailored to suit your organization’s unique needs.

Assign data governance roles with intention — these five questions get you started.

Consider factors such as:

• Existing Skills and Expertise: Assess the skills and expertise of your team members to determine the most suitable roles for them. Look for individuals with relevant experience, domain knowledge, and technical proficiency to fill specific roles effectively. Consider providing training or professional development opportunities to bridge any skill gaps and to enhance the team’s capabilities in data governance practices, regulatory compliance, data management tools, or any other relevant areas. This investment in skill development will not only enable individuals to perform their roles effectively but also contribute to the overall success of the data governance initiative.
• Accountability and Authority: Clearly define the scope of responsibilities for each role and ensure that individuals have the necessary authority to fulfill their duties. Align accountability with decision-making power to enable timely and efficient execution of data governance activities. Utilize tools like the RACI (Responsible, Accountable, Consulted, Informed) matrix to prevent overlaps and ensure that everyone remains aligned and informed about their respective responsibilities.
• Collaboration and Communication: Data governance is a collaborative effort that requires effective communication and coordination among team members. Consider assigning roles that promote collaboration and facilitate seamless communication between different stakeholders within the organization.
• Scalability and Flexibility: Anticipate future growth and changes in your organization’s data governance needs. Assign responsibilities in a way that allows for scalability and flexibility, so that the team can adapt to evolving requirements and effectively manage expanding data governance initiatives.
• Continuous Evaluation: Define key performance indicators (KPIs) that align with the goals and objectives of the data governance program and regularly evaluate the effectiveness of role assignments and adjust responsibilities as needed. Solicit feedback from team members, stakeholders, and senior management to ensure that roles are aligned with organizational goals and deliver the desired outcomes.

As AI becomes more embedded in data workflows, consider including training on how governance intersects with AI systems — such as understanding how data quality impacts model accuracy, or how AI tools can assist in governance tasks like data classification or quality monitoring.

Training & Development for Data Governance Roles 

For most, implementing a data governance program involves introducing new roles that often lack clear guidelines. To build a skilled and capable data governance team, it is crucial to prioritize continuous training and development.

Consider the following:

• Orientation Program: Create a comprehensive orientation program for new and existing team members that will introduce them to the organization’s data governance strategy, goals, and key stakeholders. It should also provide an overview of the team’s roles and responsibilities, as well as any existing policies and procedures.
• Tool Training: Depending on the technological frameworks already in place in your organization, it becomes essential to provide tool training to team members. This training helps familiarize them with the software and tools that are necessary for effective data governance implementation.
• Cross-Functional Training: Data governance teams often work closely with other departments — such as IT, legal, compliance, and business units. Provide cross-functional training to team members to help them understand the perspectives, challenges, and requirements of all stakeholders. Use tools such as a data dictionary, data catalog, and business glossary to better manage data assets, their application, and related metadata. This knowledge will enable team members to collaborate effectively and align data governance efforts with the overall organizational objectives.
• Mentoring and Shadowing: Pair new team members with experienced data governance professionals who can serve as mentors. This allows them to learn from experienced practitioners, understand best practices, and gain insights into the practical aspects of data governance. Shadowing these mentors during their day-to-day activities can provide valuable hands-on experience.
• Industry Training and Certifications: Encourage team members to pursue industry-specific training and certifications related to data governance. This can enhance their expertise and credibility, as well as keep them updated on the latest trends and practices in the field. Offering financial support or resources for such training can further motivate team members to invest in their professional development.
• Continuous Learning Opportunities: Establish a culture of continuous learning within the data governance team. Encourage team members to attend conferences, webinars, and workshops, and provide access to relevant resources and educational materials. Additionally, consider organizing internal knowledge-sharing sessions or lunch-and-learn sessions where team members can share their expertise and learn from one another.

Not every org needs every role — use this guide to grow your governance team at the right time.

Take A Practical and Proportional Approach to Building Your Team

For a data governance program to be successful, it should be realistic – it should match your company’s needs, size, urgency, maturity, and capabilities. This includes the staff and resources you are dedicating to your efforts.

You likely don’t need an individual in every role outlined above – just yet. As data governance activities expand and more people take on data governance responsibilities, assess the need to add functions and scale your team.