Welcome to Mind Map: A DataGalaxy blog series where we’ll deep dive into creating an effective, secure, and high-quality data governance framework for data experts, project coordinators, and data decision-makers.

In this step-by-step blog series, we’ll discuss the key pieces needed to build an effective data governance framework – Whether you’re just getting started or looking to update your current plan.

This is step two: Establishing a Data Governance Team. Discover step one: Understanding Business Goals and Objectives and the rest of the CDO Mind Map series!


Establish a data governance team

After understanding how to connect your data governance plan with organizational goals and objectives, the next step is to build a data governance team, a critical task for a Chief Data Officer (CDO). However, this can uncover some unforeseen challenges for CDOs. Keep reading to uncover these challenges and gain insight into avoiding and mitigating these risks.

Creating a data governance framework

Establishing a clear and effective data governance framework that aligns with the organization’s objectives and culture can be complex. This framework should address data stewardship, data policies, and data management processes, but can be difficult to completely establish while in a time of transition. Some roadblocks may arise, including:

  • Lack of clarity on goals and objectives: Without clear goals and objectives for data governance, it is challenging to create a framework that aligns with the organization’s strategic vision, and the absence of a clear direction can result in a disjointed framework.
  • Organizational complexity: Large or complex organizations may have diverse data ecosystems, departments, and data sources, and harmonizing these various elements into a unified framework can be complex and time-consuming.

To mitigate these risks, CDOs can quickly define roles, responsibilities, and reporting structures clearly within the framework; prioritize data quality and consistency by establishing data standards; and involve legal and compliance teams to ensure alignment with regulatory requirements early on in the creation process.

Resource constraints

Securing budget and resources for building and maintaining a data governance team can be challenging. Many organizations may not fully understand the value of data governance and may be reluctant to invest in it.

Limited budget allocation for data-related initiatives can restrict the CDO’s ability to hire and retain qualified data governance professionals. Data governance requires investments in personnel, technology, and tools, which can strain the organization’s financial resources. To avoid setbacks caused by resource constraints, CDOs can:

Data silos

Data silos, isolated pockets of data that are not easily accessible or shared across the organization, can often occur when CDOs attempt to create a data governance team. Breaking down these data silos and ensuring cross-functional collaboration can be a major challenge. However, there are a few key points CDOs can follow to mitigate this risk:

  • Encourage collaboration and communication among different departments and teams to promote a culture of data sharing.
  • Invest in technology and tools that enable data integration and ensure that data governance practices are compatible with existing data systems.
  • Appoint data stewards within each department or team to take responsibility for data quality, ownership, and compliance with data governance policies.

Data privacy & compliance

With the increasing focus on data privacy regulations (e.g., GDPR, CCPA), CDOs need to navigate the complex landscape of data compliance, which can be legally and operationally challenging. Regulatory compliance is a critical aspect of data governance, particularly in industries and regions with stringent data protection and privacy laws.

By taking these steps and proactively addressing regulatory compliance challenges, a CDO can assemble a data governance team that is better equipped to navigate the complex landscape of data regulations and ensure that the organization remains compliant with relevant laws:

  • Hire compliance experts: CDOs can seek to employ team members with expertise in data compliance, privacy, and regulatory matters.
  • Training & awareness: Invest in training and awareness programs to ensure that the team understands and adheres to relevant regulations.
  • Ongoing monitoring: C-level data professionals should seek to establish processes for ongoing monitoring and auditing of data governance activities to ensure compliance.

Cultural resistance

Changing the organizational culture to prioritize data governance can be difficult. Some employees may be resistant to new processes and policies, but resistance to change is a common challenge in many organizations, and it can be particularly pronounced when introducing new data governance practices. This resistance to change may present itself as a fear of job disruption, refusal to complete training, or overall fatigue.

A CDO can take the following steps to help mitigate resistance to change and create a more supportive environment for assembling and implementing a data governance team within the organization:

  • Communicate clearly: Clear communication of the reasons for data governance initiatives, their benefits, and the expected impact on employees’ roles and the organization as a whole is imperative for sparking organizational change.
  • Involve stakeholders: Involve relevant stakeholders and employees in the decision-making process, ensuring that their perspectives are considered and addressed
  • Provide training & support: Offer training and support to help employees adapt to the changes – This can include training on new processes, tools, and skills required for data governance.
  • Address concerns: Actively address concerns and questions from employees, providing reassurance and clarifications as needed.
  • Lead by example: Demonstrating commitment to data governance from top leadership sets an example for the entire organization! Inspire your teams to embrace changes in policy, not fear it.

Data ownership

Defining and assigning data ownership is often a contentious issue: Different departments may have conflicting interests when it comes to data control, and CDOs may encounter conflicts when determining who has the authority and responsibility for various data assets. This can lead to increased data silos, data quality issues, and an upcoming change in organizational structure.

To address data ownership issues when assembling a data governance team, a CDO can take the following steps:

  • Define data ownership: Clearly define data ownership roles and responsibilities to outline who is responsible for what aspects of data, and communicate this across the organization.
  • Collaboration & education: Engage with data owners to educate them about the benefits of data governance and the role of the data governance team in supporting their efforts.
  • Establish data stewardship: Appoint data stewards within departments or teams to facilitate collaboration between data owners and the data governance team.

Talent shortages

Finding and retaining individuals with the necessary skills and expertise in data governance can be challenging, as the demand for such professionals often exceeds the supply. CDOs may experience talent shortages when assembling a data governance team due to several factors related to the high demand for data professionals and the specific skill set required for effective data governance, including:

  • A growing demand for data professionals: The increasing recognition of the value of data and data-driven decision-making has led to a surge in demand for data professionals. Organizations across various industries are often competing for the same pool of talent, resulting in shortages.
  • Specialized skill set: Data governance requires a unique skill set that includes expertise in data management, compliance, data quality, and data privacy. Finding individuals with the right combination of skills and experience can be challenging.

To address talent shortages when assembling a data governance team, a CDO can consider the following strategies:

  • Upskilling existing staff: Invest in training and upskilling existing employees who have the potential to take on data governance roles.
  • Collaborating with educational institutions: Partner with universities and colleges to help shape educational programs that produce graduates with relevant data governance skills.
  • Considering remote work: Expanding the search for talent beyond local geographic constraints can help access a broader pool of candidates.

Communication & education

Educating employees at all levels about the importance of data governance and ensuring effective communication about data-related policies and changes is crucial. However, a Chief Data Officer may encounter communication challenges when assembling a data governance team due to several factors related to the complexity and interdisciplinary nature of data governance, including:

  • Interdisciplinary nature: Data governance encompasses various disciplines, including data management, compliance, data quality, privacy, and security. Team members may come from diverse backgrounds, making it challenging to communicate effectively across these domains.
  • Technical jargon: Data governance often involves technical and specialized terminology that may be unfamiliar to team members from non-technical backgrounds.

To mitigate risks associated with communication, CDOs can take the following steps:

  • Develop a clear communication plan: Create a communication plan that outlines how information will be disseminated, to whom, and through which channels.
  • Foster a collaborative culture: Promote a culture of collaboration and open communication within the team, and encourage team members to share their perspectives and challenges.
  • Use plain language: When communicating complex technical or regulatory concepts, use plain and accessible language to ensure understanding by team members with diverse backgrounds.

IT integration

Integrating data governance tools and technologies into existing systems and workflows can be technically challenging and may require significant effort and communication within any data professionals’ teams. However, IT integration is crucial in the context of data governance as it involves connecting various systems, databases, and technologies to ensure data is managed, accessed, and protected effectively.

Challenges may arise when switching from a legacy system, keeping up with ever-changing compliance requirements, and finding skilled IT professionals. To address IT integration challenges when assembling a data governance team, a CDO can take the following steps:

  • Data mapping & profiling: Perform data mapping and profiling to understand the structure and relationships of data across systems.
  • Data catalogs & metadata management: Implement data catalogs and metadata management to document data sources, data definitions, and data lineage, which can help with integration.
  • Involve IT experts: Engage IT professionals and experts in the integration process – Collaborate with the IT department to ensure alignment with broader IT strategies and business objectives.

Measuring success

Defining and measuring the success of a data governance program is important, but can often be elusive. CDOs and their teams need to establish key performance indicators (KPIs) that reflect the impact of data governance on the organization. Measuring KPIs is critical for assessing the effectiveness of data governance efforts, ensuring alignment with organizational goals, and driving continuous improvement in data management practices – It helps CDOs and their data governance team maintain a results-driven approach and communicate the value of their work to the organization as a whole.

However, monitoring and measuring KPIs can present some challenges for data professionals working to create a data governance strategy, especially if they are trying to create concrete results with unorganized, dirty, or low-quality data. To avoid these risks associated with measuring success during a data governance initiative, CDOs can take the following steps:

  • Define clear KPIs: Define clear and specific KPIs that align with the organization’s data governance goals and objectives.
  • Create KPI dashboards: Develop KPI dashboards and reporting mechanisms to visualize and communicate KPI results to stakeholders.
  • Implement cross-functional collaboration: Collaborate with various departments, especially IT and compliance, to ensure that KPIs reflect the shared goals of the organization.


To address these challenges, CDOs and data professionals should focus on developing a clear data governance strategy, securing executive support, and aligning data governance initiatives with the organization’s business goals.

Interested in learning more? Follow along with our step-by-step blog series about building an effective data governance framework!

Learn even more about using your data as an asset to achieve higher levels of data governance and data quality. Book a demo today to get started on your organization’s journey to complete data lifecycle management with DataGalaxy!