Sep 24, 2025
Data Governance: Bureaucracy or competitive advantage?
A practical look at data governance, its challenges, regulations, strategic importance, and opportunities.
In many companies, it’s often said: “data is key, but governance is pure bureaucracy.” Yet, when we dig into the challenges of using data, we find issues like duplicated information, legacy systems, unclear permissions, or data that doesn’t align with business logic. Can governance help address these challenges?
This article seeks to clarify what data governance is, the Colombian regulation that shapes it, and the main challenges organizations face when putting it into practice.
In practical terms, what is data governance?
The set of rules, processes, and responsibilities that ensure a company’s information is reliable, accessible, and used according to standards of compliance, ethics, and security. In short, it’s an internal manual that defines who can use what data, for what purpose, and under which conditions.
Data governance policies are shaped by regulation but usually include cross-organizational elements that go beyond what regulators require.
Let’s talk about regulation. Who regulates, and what do they establish?
The need to guarantee transparency and security of information has driven global initiatives to define protective measures and regulate data use. In Colombia, the regulatory framework takes the European GDPR and the Data Act as main references, both of which impose strict rules and heavy penalties for failing to comply with principles such as minimization, transparency, accuracy, and proactive accountability.
In Colombia, data protection regulations apply to all organizations that collect or process personal information, under the supervision of the Superintendence of Industry and Commerce. For banks and insurers, the Financial Superintendence enforces additional security and cybersecurity requirements. Organizations must register their databases in the National Database Registry (RNBD), define data treatment policies, respond to requests and claims within set timeframes, and protect information through both technical and administrative measures.
This way, Colombia is moving toward alignment with international standards, promoting stronger rights for citizens, greater responsibility for companies, and increasing attention to risks arising from AI adoption and the growing, intensive use of data.
Beyond regulatory compliance, what other challenges do we see around governance?
We will focus mainly on the challenges faced by large organizations. But first, it is worth briefly mentioning an approach for micro, small, and medium-sized enterprises (SMEs) to establish clear governance practices from the early stages.
For SMEs that collect data and want to use it efficiently while complying with regulations, the challenge lies in designing policies with limited resources and applying the principle of privacy by design. This means asking not only what data is needed to operate today, but also how scalable the system will be when the company has ten times more users and must comply with stricter regulations.
In a mature organization, the challenge is not building from scratch, but managing existing systems and infrastructures, and dealing with vast amounts of customer or user data. Here we often find legacy systems, poor data quality, and business complexities that make it difficult to ensure consistency and security of information.
The practices we see as key to addressing these challenges are:
- Identify legacy systems: quickly map out what information exists, where it is stored, and who uses it.
- Eliminate duplicates and set cleaning rules: reduce noise and document these processes clearly to support audits and provide context for internal data users.
- Early-stage federated governance: appoint data stewards in each area to build bridges between Business, Compliance, and IT, without over-centralizing in teams that lack full context.
- Organizational culture: training to raise awareness about legal and reputational risks is essential. Sharing governance policies also facilitates efficient and effective use of data.
- Monitoring: establish metrics on data quality, consistency, usage, and access to create visibility, provide objective input to refine governance policies, and demonstrate results.
Is governance just a mandatory, boring topic with no real business impact?
In many organizations, data governance is associated only with complying with regulations and avoiding penalties. However, what we see in practice is that its impact goes much further. Well-implemented governance does much of the heavy lifting needed to develop robust, reliable analytics solutions—from automated reporting to predictive models and AI agents trained with high-quality data.
Do you want our consultants to help you with this?
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Felipe Uribe Velásquez
Director
Camilo Monsalve Maya
Data Engineering Consultant
