Dunsin Opebiyi Shared His Experience on Data Governance

Can you introduce yourself?

My name is Dunsin Opebiyi. I am a results-driven Data Governance and Data Product Manager with over 7 years of experience across various industries including SaaS, EdTech, Facility Management, and Finance.

Before transitioning into data governance, I previously had over 8 years combined experience as a finance and project analyst. I was also a relationship manager for a couple of years in the banking industry.

As a data governance professional, my primary focus is on developing and implementing data strategies that ensure regulatory compliance while optimizing business operations. This involves creating policies and frameworks to manage data quality, security, and accessibility, ensuring data is accurate, compliant with regulations like GDPR, and available to the right people at the right time. I also work closely with cross-functional teams to ensure that governance practices align with business objectives, enabling data-driven decision-making across the organization. Ultimately, I help organizations leverage data as a valuable asset.

I am also a co-founder of an EdTech and mentoring platform, helping young professionals navigate data management challenges. I also recently founded a SaaS company, with the vision of providing an agile, adaptable, and easy-to-use data governance tool.
I am a data and digital technology enthusiast and I am deeply involved in the UK and Nigeria digital tech ecosystem. I frequently speak on Data Protection, Governance, and AI at industry conferences and various platforms.
 
Can you tell us about your background and how you came into data governance?

I began my career in banking, which gave me a strong foundation in managing data and ensuring compliance. It also exposed me to the importance of proper data management especially as it concerns the quality of data. Looking backnow, I would say my value and appreciation for data has its background in my banking experience. Being a heavily regulated industry and due to the sensitivity of customers’data, everything about data in banking requires priority and sensitive treatment from creation throughout the data lifecycle.

I later proceeded into financial and project analyst roles. These roles also further drove my desire to be involved in the management of data as I discovered the limitations of analysis without quality data. Analysis and the insights generated from it can only be as good as the quality of data input. This deepened my desire to get involved in data management, especially as it concerns ensuring data are of good quality, fit for purpose, and trustworthy.
So, I will say my journey into data governance was sparked by the realization of the pivotal role data plays in today’s decision-making processes. In my previous roles, I saw firsthand how organizations could leverage data to drive business value. However, I also witnessed the chaos that ensues when data is poorly managed. This inspired me to transition into data governance and since then I have been involved in establishing and implementing robust data governance frameworks that ensure data integrity, security, and compliance, ultimately enabling organizations to harness the true power of their data. My first role as a Data Governance Analyst allowed me to focus on data discovery and quality metrics. Since then, I have worked across industries, gradually moving into leadership roles where I could shape data strategies and governance frameworks to meet business needs and compliance standards.

I am also currently leveraging and applying my skills, experience, and certifications in projects and productmanagement to further drive my impact in data governance by exploring data product management in such a way that produces easy-to-use data governance tools for data governance professionals.

How do you define success in Data Governance?

When I talk about successful data governance, I am not just thinking about some strict rules, policies, or processes. It isabout creating an ecosystem where data is accurate, trusted, and valuable to the entire organization. Essentially, success in data governance is about creating a culture where data is recognized and used as a strategic asset across the organization. In this environment, every team understands the value of accurate, secure, and compliant data, and governance is not seen as a bottleneck but as an enabler of better decisions.

To me, success in data governance starts with having clear policies and standards that guide how data is handled, from collection to storage and beyond. These policies ensure that data remains high-quality and trustworthy, which is crucial because, without quality data, even the best analysis or AI tools will fail. Data quality is a key measure of governance success. When teams can consistently rely on data to make decisions, that’s when you know your governance framework is working.

Another core pillar of successful data governance is regulatory compliance. Given today’s evolving data privacy laws like GDPR or CCPA, it’s critical to ensure that data is managed in ways that comply with all relevant regulations. But this is not just about avoiding fines, it is much more about building trust with customers and stakeholders. When your governance framework ensures compliance, it signals to the market that your organization values privacy and data protection. This enhances your brand reputation.

Beyond policies and compliance, engaging stakeholders throughout the organization is crucial. Data governance must be collaborative. I make sure that I’m engaging the right people early in the process, whether it is IT, marketing, or legal, so that everyone understands their role in data stewardship. When stakeholders are actively participating in governance initiatives, it creates a shared responsibility for data integrity and usage. This active stakeholder engagement is one of the strongest indicators of success in governance because it shows that data is being handled thoughtfully at every level.

I will also add that data governance must evolve as the organization grows and as new challenges or technologies emerge. What worked yesterday may not be sufficient tomorrow, especially with advancements like AI. The best governance frameworks are flexible and adaptable, able to incorporate new technologies, business models, and regulatory changes seamlessly.

In summary, successful data governance is a dynamic, collaborative process that empowers teams to use data confidently and responsibly, while supporting the organization’s broader goals. It’s an evolving journey, but one that ensures data truly drives business value.
 
What key metrics do you use to measure data governance effectiveness?

When it comes to measuring the effectiveness of data governance, I believe it is essential to go beyond just tracking policies and processes. The true value of data governance lies in how it improves business outcomes, so I focus on metrics that reflect the health of the data and its impact on the organization.

Firstly, I rely heavily on data quality scores. These metrics give us insights into how accurate, complete, and consistent the data is. When data quality improves, it directly enhances decision-making and operational efficiency. Whether it isreducing duplicate records, ensuring consistent formats, or maintaining up-to-date information, these scores are critical in identifying where governance efforts are paying off.

Secondly, compliance rates are a key metric, especially with the increasing regulatory landscape around data protection, such as GDPR. I track how well the organization adheres to these regulations. A strong compliance record is not just about avoiding fines, it builds trust with customers, stakeholders, and regulators. Regular audits help me monitor whether data governance policies are aligned with these legal frameworks.

User engagement metrics are also important. It is one thing to have policies in place, but governance is only effective if people across the organization are actually using those policies. I track how often users interact with governance tools, how frequently they request data, and how well they adhere to the established governance processes. This gives mea sense of how embedded governance practices are within the company culture.

Another critical measure is the reduction in data-related risks and incidents. This can range from a decrease in data breaches to a reduction in data inaccuracies that impact business decisions. Tracking how often these incidents occur helps demonstrate how well governance is mitigating risks.

Finally, I always keep an eye on how governance affects business outcomes. For example, are our governance efforts helping to reduce operational costs? Are they improving decision-making across teams? By linking governance metrics directly to business performance, we can show its tangible value beyond compliance or process improvements.

In conclusion, the metrics I focus on are data quality scores, compliance rates, user engagement, risk reduction, and business impact. These metrics help create a narrative that shows how data governance is driving real value. It is about making governance not just a background function but a strategic enabler for the organization’s success.
 
Can you explain the role of data governance in risk management?

Data governance plays a crucial role in risk management by establishing policies and frameworks that protect data integrity, security, and compliance. In today’s digital landscape, data breaches, inaccuracies, and non-compliance can lead to severe financial, legal, and reputational risks. By implementing a strong data governance strategy, organizations can identify potential vulnerabilities, whether it is data access, storage, or sharing and mitigate these risks through structured processes like access controls, data encryption, and regular audits.

For instance, effective data governance ensures that data is handled in compliance with regulations such as GDPR, minimizing the risk of regulatory penalties. It also establishes data classification standards, ensuring sensitive information is adequately protected. From a business perspective, risk management in data governance is about not only safeguarding the organization from potential threats but also ensuring that data is reliable and trustworthy for decision-making.

Additionally, data governance provides visibility into data flows, which is essential for assessing risks tied to data usage or breaches. By establishing data lineage and audit trails, you can track how data is used, who accesses it, and where potential risks might arise. This gives the organization the ability to respond quickly to incidents, reducing the overall impact of any data-related risk.

In summary, I will say, data governance integrates deeply into risk management by identifying, mitigating, and controlling risks associated with data, ensuring the organization’s data is not only secure but also an asset that drives business value.
 
How do you ensure data quality, security, and compliance in product design?

In product design, I ensure data quality by implementing robust data governance frameworks. I implement strict validation processes and automated checks to detect inaccuracies early. I also ensure regular data audit is conducted. In terms of security, I collaborate with IT teams to apply encryption, role-based access controls, and regular vulnerability assessments. This ensures the product meets high-security standards from development through launch.When it comes to compliance, I make sure the product aligns with regulations like GDPR right from the planning phase by embedding privacy by design principles, ensuring all legal and regulatory requirements are embedded into the product’s architecture, conducting risk assessments, and providing regular training on data protection to all stakeholders. This approach ensures that data is accurate, secure, and compliant throughout the product lifecycle.
 
 
What data privacy regulations should be considered when developing products or in general (e.g., GDPR, CCPA)?

Either in product design or in general, the essential data privacy regulations will depend on the industry and target region. In general, the key regulations to consider includeGDPR (General Data Protection Regulation) for EU users, focusing on user consent, data minimization, and the right to be forgotten. CCPA (California Consumer Privacy Act) for US-based users, emphasizing transparency, data access, and deletion rights. PIPEDA (Personal Information Protection and Electronic Documents Act) in Canada, governs the collection and use of personal data. I ensure these are built into the product from the ground up through privacy by design principles  

I cannot exhaust even the popular and common ones but like I said the region and the industry determine the regulations to focus on. In the UK for instance, emphasis will always be on GDPR and the UK Data Protection Act 2018 no matter the industry. We also have close equivalents of these regulations in other regions including Nigeria. These laws focus on user rights, data transparency, and accountability. Key areas include obtaining user consent, implementing data protection impact assessments (DPIAs), and ensuring data minimization and accuracy. It is also essential to ensure data portability and the right to erasure are integrated into products. Additionally, it is important to adhere to sector-specific guidelines such as those for financial data (FCA regulations) or healthcare data (NHS Data Protection protocols) in the UK, to ensure comprehensive compliance .
 
What qualities do you look for when hiring data governance analysts?

As I said I co-founded an EdTech and mentoring platform, soI am involved in training, preparing, and mentoring young data management professionals for interviews and a successful career in data governance.

When hiring data governance analysts, there are many things Ilook for. These include core data governance proficiency and knowledge, technical skills, analytical skills, communication,and problem-solving skills.

The core data governance skills relate to the candidate’s proficiency in areas like data quality, policy, data governance framework development, and implementation among others. The ability to effectively use data governance tools is also very essential. Technical skills and proficiency in SQL for instance, for data quality management, will be a good advantage.

A data governance professional must be strong analytically. I will look for the ability to interpret data, identify inconsistencies, and propose solutions. The candidate’s ability to logically and analytically relate and appreciate data is key.A good data governance analyst also requires proper attention to detail to ensure data accuracy and compliance with regulations like GDPR.

Communication may sound very basic but stakeholder communication skill is perhaps the most essential of the skills I will be looking out for in a data governance professional. Collaboration with technical and non-technical teams is at the centre of the role, therefore mastery of communication is required and it is unnegotiable. I will also assess the candidate’s problem-solving skills. This involves addressing data-related challenges and driving process improvements efficiently .
 
How do you ensure data accessibility and usability?

To ensure data accessibility and usability, I focus on a few key areas which include data cataloging. This is easily implemented using data governance tools like Collibra to create an organized, understandable, and searchable data inventory. I also ensure I set up adequate access control. Access control is simply setting up permissions to ensure secure yet flexible data access depending on roles . I also implement intuitive platforms in order to have user-friendlydashboards and interfaces. Intuitive dashboards like Tableau, Power BI enhance not just accessibility and usability but alsoeasy interpretation of data.

I further ensure the roles maintaining data quality and accessibility across departments are in place through well-implemented data stewardship. The place of training to ensure users understand how to find, use, and interpret the data effectively cannot be overemphasized. I take data literacy very seriously and ensure all stakeholders in my organization have adequate training. In fact, due to its importance, data literacy is one of the key topics I enjoy speaking about at speaking engagements in Nigeria, the United Kingdom, and every other place I have the platform.
 
What are some common challenges data governance professionals and managers face and how do you overcome them as a young data governance professional?

There are many challenges data governance professionalsface. In fact these challenges stem from the complexities and dynamics of the profession itself.
Navigating complex regulations like GDPR and industry-specific guidelines can be very challenging, especially in industries that are heavily regulated. Interpreting and incorporating these many regulations and guidelines into your process to ensure compliance can be tasking especially with the pace at which regulations are changed, adjusted, and reinvented. My solution to this is building strong frameworks and staying updated on regulations. Having strong framework in place, helps me to have a structure through which I apply changes in regulations easily. As a young data governance professional, it is crucial to be abreast of regulations especially as related to your industry. This is a delicate area that must be given close attention as a miss or inadequate capture of regulation can lead to a huge fine and dent oncorporate brand or far worse.

Another big challenge is maintaining data quality and consistency. Maintaining high-quality data across multiple sources is tough. This is the core of data management as theessence of managing data revolves greatly around ensuring data is of high quality and fit for purpose. Poor-quality data can undermine governance efforts. I tackle this by setting up automated data validation and regular audits. Leveraging robust data governance tools plays a great role in this. A lot of time, I also see that young data governance professionals struggle with data Silos. It is also a major cause for low-quality data as different departments often store data separately, making it difficult to manage. The simple way toovercome this is by implementing centralized data governance frameworks.

By the nature of its functions, data governance requires a lot of cross-functional collaboration. Aligning diverse teams withdata practices can be challenging. Various teams and functions are involved in the management of data either directly or indirectly. Collaborating with both technical and non-technical teams requires some skills. As I said earlier, communication is one of the key skills required for the role of data governance. Clear communication, using appropriate mediums helps all stakeholders not only to understand but also to have clarity of scope, goals, and expected actions. Getting all department functions and stakeholders aligned on data governance practices will always be a major challenge. I address this by fostering open communication and running data literacy programs to ensure everyone understands the importance of governance.

Implementing data government frameworks and initiatives requires some change management. Embracing change could be tasking even in our personal daily lives. Getting individuals and teams to embrace and adjust to new ways can be a major challenge. There is a way they are used to it. Getting them to adjust and embrace a new way can be challenging and therefore requires a process of careful cultural change management. I ensure I engage all stakeholders properly with the benefits of the DG initiatives. One of the best ways to gain support is to highlight how a proposed DG initiative will take stakeholders pain points away and how it contributes to organisational and team goals. Everybody naturally gravitates towards benefits. Pitching benefits of the new ways over the old way will always help. Adequate training and support that ease them seamlessly into the new way of doing things is equally an essential part of managing the change.
 
What measures do you take to prevent data breaches?

To prevent data breaches, my approach revolves around a combination of proactive measures and best practices that prioritize both security and operational efficiency. First, encryption is key. By encrypting all sensitive data both at rest and in transit, we ensure that even if data is intercepted, it’s unreadable without the right encryption keys. This way, weare safeguarding the data whether it is stored or being transmitted across networks. Access controls are equally critical. By implementing role-based access, we ensure that only authorized personnel with a legitimate need can access or manipulate sensitive information. This minimizes the risk of internal mishandling or exposure.

We also conduct regular security audits and vulnerability assessments. These are like health check-ups for our systems, helping us proactively identify and patch any potential security gaps before they can be exploited.

For non-production environments, where sensitive data is often used for testing, IT deploys data masking. This process anonymizes sensitive information, reducing the exposure risk while allowing teams to still work with functional data.

Finally, one of the most important measures is continuoustraining. No matter how proactive we are, human error is always a factor. I always emphasize training all users and stakeholders on recognizing threats like phishing attempts, proper data handling, and security hygiene, which strengthens overall defence against breaches.

It’s a combination of technical safeguards, ongoing monitoring, and a culture of awareness that helps to stay secure in an increasingly complex digital landscape.
 
How do you communicate data governance policies to stakeholders?

As a data governance professional, clear communication with stakeholders is key to the success of any governance initiative. My approach is to tailor the message based on the audience, ensuring that everyone, from executives to technical teams, understands the importance of data governance in a way thatis relevant to their role.
For executive leadership, I focus on the strategic impact of data governance. I explain how governance helps mitigate risks, improve decision-making, and ensure compliance with regulations, which ultimately protects the organization’s reputation and bottom line. I use metrics like data quality improvements, reduced risk exposure, and cost efficiencies to demonstrate the tangible value of strong governance policies.

For business teams, I emphasize how data governance supports their day-to-day activities. I communicate how better data quality, consistent definitions, and standardized processes make it easier to get accurate insights and drive business decisions. I often frame governance as a way to unlock the potential of data rather than just a compliance requirement.

When speaking with technical teams, I get into the details of policy implementation, whether it’s about encryption standards, data access controls, or data lineage. I highlight how governance policies help ensure data is handled properly and securely at every touchpoint. This also includes communicating clear guidelines for data collection, storage, and sharing.

To ensure these policies are well-understood I use various communication mediums as appropriate. I organize training tailored to specific groups, where we dive into practical applications of governance policies and how they relate to the team’s work. I also create easy-to-understand guidelines and make them available on internal platforms, ensuring they are regularly updated. I follow these up by regular check-ins. Data Governance is not a ‘set it and forget it’ process. I maintain ongoing communication through regular meetings and feedback loops to address any challenges or questions that arise.
By customizing the way I communicate data governance, I ensure that everyone feels invested in the policies, understands their role in compliance, and sees the value of strong data practices.
 
How do you handle resistance to data governance initiatives within an organization?

Handling resistance to data governance initiatives often comes down to addressing the root causes of the resistance. Usually,it relates to misunderstanding or fear of added bureaucracy. My approach is to prioritize transparent communication and involve stakeholders from the very start. I explain how governance is not just about compliance but also about making their work easier and more efficient, ensuring they can trust the data they are working with. Sharing quick winsor examples of how data governance has solved specific problems helps build trust and buy-in.
I also make sure to involve data governance sponsors and key influencers within departments, people who are respected and whose opinions carry weight. When they advocate for the governance initiatives, it creates momentum. Engaging these internal champions helps shift the mindset from seeing governance as restrictive to seeing it as an enabler that supports innovation and ensures better decision-making.

Ultimately, it is about creating a collaborative environmentwhere governance is seen as a tool that empowers, rather than a set of rigid rules to follow. By emphasizing that data governance will improve data access, reliability, and compliance without adding unnecessary roadblocks, we can build an organizational culture where governance is embraced rather than resisted.
 
How do you integrate data governance into product development lifecycles?

Data governance is an essential part of the product development lifecycle, not just an afterthought. From the very beginning, I work closely with product and engineering teams to ensure that data governance principles are built into every stage of the process.

For example, during the planning phase, we assess what types of data will be collected, how it will be used, and what regulatory or compliance requirements apply. This helps us ensure that we are only collecting data that is necessary for the product’s functionality, aligning with data minimizationprinciples. We also evaluate privacy concerns early on, especially if the product will handle sensitive information.

In the design phase, I advocate for privacy-by-designpractices, where we embed privacy and security features directly into the architecture of the product. This could mean using data masking techniques or anonymization to protect sensitive data in non-production environments, or ensuring that data is encrypted and access controls are in place from day one.

As we move into the development and testing phases, I collaborate with developers to ensure that data quality standards are upheld and that data is handled according to governance policies. We continuously monitor for risks such as improper data handling, data silos, or access issues. This includes performing regular audits and vulnerability assessments to catch any potential issues.

Finally, in the deployment and post-launch stages, we continue to monitor compliance with data governance standards. We conduct regular reviews of data usage, ensuring that access is restricted to the appropriate users through role-based access controls and that our data remains secure and compliant with regulations like GDPR for instance.

By integrating data governance throughout the product lifecycle, we not only ensure that the product is compliant and secure, but we also create a culture of data stewardship across teams. This proactive approach helps mitigate risks, improves data quality, and supports the long-term success of the product.
 
How do you balance data governance with product innovation and speed-to-market?

As a data governance professional, one of the biggest challenges is striking the right balance between rigorous governance practices and the need for innovation and speed-to-market. I see data governance not as a blocker, but as an enabler of sustainable innovation. When done right, it helps accelerate product development by ensuring that teams can trust the data they are working with and that it is handled in a compliant and secure way from the start.
To achieve this balance, I integrate governance into the product development lifecycle early on. This means that from the very first stage of ideation and design, we are thinking about data governance, whether it is related to privacy-by-design principles, data quality, or security measures. By embedding governance into these early stages, we avoid last-minute compliance bottlenecks, which can slow down a product launch.

A big part of this is being agile in our governance approach. Rather than imposing rigid, one-size-fits-all rules, I work with product teams to understand their specific needs and adapt governance frameworks to support speed and flexibility. For instance, we might use automated governance tools or AI-driven compliance checks that help teams move quickly without sacrificing data security or compliance.

I also focus on fostering a collaborative relationship between data governance and product development teams. By working closely with them, I can ensure that governance requirements are met without stifling innovation. For example, we streamline processes like data access approvals or ensure that we are only collecting and using the data that is necessary for the product’s functionality (following data minimization principles). This keeps things efficient and reduces unnecessary complexity.

Lastly, education is key. I make sure that product teams understand the value of data governance, not just as a compliance requirement, but as something that supports product innovation in the long term. A strong governance framework ensures that we are building products responsiblyand creating a foundation of trust with users. By framing governance in this way, it becomes a natural part of the innovation process, rather than something that is seen as an afterthought or hindrance. Ultimately, good data governance allows us to innovate with confidence, knowing that we arenot exposing the company to unnecessary risks or compliance issues. It is about creating a culture where governance and speed go hand-in-hand to drive successful, secure product launches
 
If you discovered a data breach in your product, what steps would you take?

If I discovered a data breach in a product, my first priority would be to contain the breach and assess the scope of the impact immediately. Time is of the essence, and a quick response can help minimize damage and prevent further data exposure. I will initiate an incident response plan, which outlines roles, responsibilities, and actions to take in case of a breach. This involves assembling a cross-functional team that includes IT, security, legal, compliance, and communication experts to handle different aspects of the breach. I would work closely with the technical teams to isolate affected systems to stop the breach from spreading further. This might mean temporarily shutting down certain services, restricting access, or changing passwords to protect sensitive data while we investigate the root cause.

Next, it is crucial to determine how the breach occurred, that is identifying the root cause. Leveraging the technical team’s capability, a thorough forensic analysis would be conducted to understand whether it was caused by a vulnerability in our systems, human error, or a targeted attack. This helps us address the immediate issue and prevent future breaches. If the breach involves personal data, it is essential to notify affected individuals as quickly as possible. Transparency is key here. People need to know what happened, what data may have been compromised, and what steps they can take to protect themselves. We would also inform regulatory authorities, and other relevant bodies, depending on the legal requirements in the region.
Remediating the issue becomes a priority once we haveidentified the root cause. The IT would move swiftly to fix the vulnerability. This might include patching systems, tightening access controls, or updating encryption protocols. At the same time, we would monitor the situation closely to ensure the breach is fully contained and the issue is resolved.

After the breach is addressed, I would lead a comprehensive review of our security and governance policies to identify any gaps. This could involve strengthening encryption, revisiting access control policies, and ensuring all employees are trained on data security best practices. We would also conduct a post-incident review to learn from the breach and improve our overall data governance strategy. Communicating the lessons learned is very important. Both internally and externally, I would communicate what we learned from the breach and the steps we have taken to prevent future incidents. For employees, this could involve additional training, while external communications would focus on rebuilding trust with customers and partners.

In any breach situation, the key is to act quickly, be transparent, and take steps to ensure it does not happen again. Data breaches can be damaging, but how you respond is crucial to maintaining trust and protecting your organization’s reputation.
 
How do you stay current with emerging data governance technologies and trends, especially in Nigeria?

As a data governance professional, staying current with emerging technologies and trends is essential, especially in a rapidly evolving landscape like Nigeria, where digital transformation is gaining momentum. I try as much as possible to keep myself informed and ahead of the curve.
I participate actively in Industry Communities. I engage with local and global data governance communities to exchange knowledge and stay updated on the latest best practices and innovations. This includes attending conferences, webinars, and workshops, both virtually and in person. I also follow key industry groups such as the Data Management Association (DAMA UK) and forums like ISACA Lagos Chapter for the latest insights on data governance, privacy, and compliance in Nigeria and beyond.

Nigeria has a growing community of data professionals, and I make it a point to network with other experts in the field. This includes collaborating with legal professionals, data privacy experts, and cybersecurity specialists who understand the local regulatory landscape, such as Nigeria’s Data Protection Regulation (NDPR). These collaborations give me a deeper understanding of how emerging trends like AI, cloud adoption, and data privacy are shaping governance practices locally.

I ensure I stay informed about global trends in data governance, such as the rise of AI-driven governance tools, automation, blockchain technology, and data privacy regulations. However, I am mindful of adapting these trends to the Nigerian context, where challenges like data infrastructure, regulatory compliance, and digital literacy can be different. This requires a tailored approach when applying global practices locally, ensuring they are practical and relevant.

I make it a priority to pursue certifications and courses on the latest technologies and frameworks. For example, I stay current with certifications in data governance and privacy management.

In Nigeria, regulations like the NDPR are constantly evolving, so I keep a close eye on updates from the National Information Technology Development Agency (NITDA) and other government bodies. I also follow discussions around potential new legislation and global frameworks that could impact Nigerian businesses, such as GDPR-style laws that may influence local governance requirements.

Another way I stay sharp is by mentoring others and actively sharing knowledge. By training and mentoring young professionals or colleagues interested in data management, I stay engaged with new ideas and challenges from their perspectives, which helps me remain innovative and aware of trends impacting the next generation of data leaders.

Staying current in data governance is about a continuous learning mindset, always keeping an ear to the ground for new technologies, regulatory shifts, and industry trends and then figuring out how best to apply them in a local context like Nigeria and also in the United Kingdom where I am equally very active. It is exciting to see how the Nigerian market is growing, and I am always looking for ways to leverage new advancements to support that growth responsibly and securely.
 
What advice would you give to aspiring data governance professional?

I will advise them to have a solid understanding of data governance principles, such as data quality, data privacy, and compliance. Familiarize yourself with key frameworks like the DAMA-DMBOK (Data Management Body of Knowledge) and regulations like GDPR and the NDPR in the Nigeria context. These foundational concepts will be critical as you navigate your career.

Also have strong foundational technical skills. In today’s data-driven world, having technical skills is a significant advantage. Ensure you are familiar with data governance technologies such as data catalogs, data lineage tools, and data quality platforms and also have a foundational working knowledge of data management in data storage, architecture, modelling and design among others to enable you to relate and collaborate well with technical teams.

Beyond technical knowledge, strong soft skills are crucial in data governance. Skills like communication, collaboration, and critical thinking can help you work effectively with cross-functional teams, manage stakeholder expectations, and advocate for data governance initiatives. Don’t underestimate the power of networking and building relationships within your organization and the broader industry. Also realize early that the field of data governance is constantly evolving, especially with emerging technologies like AI. Subscribe to industry publications, follow thought leaders on LinkedIn, and join relevant groups and communities. This will not only keep you informed but also allow you to engage in discussions that can enhance your understanding of the latest trends.

I will also advise young professionals to seek mentorship. Finding a mentor in the data governance space can be incredibly beneficial. A mentor can provide guidance, share experiences, and help you navigate challenges as you build your career. Look for opportunities to connect with experienced professionals, whether through formal mentorship programs or informal networking events.

As a young professional, it could be challenging to get opportunities to acquire relevant experience. Practical experience is invaluable. Look for internships, volunteer opportunities, or entry-level roles that allow you to work with data governance or data management tasks. This hands-on experience will not only deepen your understanding but also enhance your resume. Consider projects that involve data quality assessments, compliance audits, or data stewardship initiatives.

Always embrace a data-driven mindset in your approach to problem-solving. Understand the value of data in driving business decisions and fostering innovation. This mindset will help you advocate for data governance best practices and illustrate how effective governance can lead to improved outcomes. The landscape of data governance is ever-changing. It is essential to be open to learning new tools and methodologies, and don’t hesitate to pivot your approach when necessary. Adaptability will be a key asset in your career as you face new challenges and opportunities.

Finally, as you gain knowledge and experience, consider giving back to the community. Share your insights through blogs, webinars, or speaking engagements. Engaging with the community not only positions you as a thought leader but also helps you learn from others’ experiences and perspectives. It also helps you to stay passionate about data governance and its impact. This field is not just about compliance; it is about empowering organizations to make better data-driven decisions, ensuring ethical data use, and enhancing customer trust. Let that passion drive you forward, and you will find fulfillment in your work.
 
What advice would you give to organizations just starting their data governance journey?

For organizations just starting with data governance, my biggest advice is to start small, but think big. Define clear, measurable objectives that align with your overall business strategy. Do not try to implement a massive governance structure all at once. It is more effective to tackle governance in stages.
Also, involve key stakeholders early on. Governance is not just a task for IT; it needs buy-in across departments to work. By fostering a culture of data stewardship, you will help everyone understand their role in managing data responsibly.

Invest in the right tools and technology that can grow with your organization. Tools for data cataloging, quality control, and compliance are essential, but so is the human side. Provide training and support so that everyone understands their role. Lastly, be prepared to iterate and adapt. Your governance framework should evolve as your organization and data needs grow.