What is data governance and why is it important?

Data governance is the practice of managing and organizing data and processes to enable collaboration and compliant access to data. It allows users to create value from data assets even under constraints for security and privacy. While technology supports it, governance is ultimately about people and process, putting the guardrails in place to mitigate risk while accelerating adoption.

Data governance is more than just organizational redtape; it is an enabler that balances data security with data value. It is the foundational discipline that supports critical business outcomes, allowing organizations to leverage their data for revenue growth and innovation while ensuring that regulatory risks are managed invisibly in the background.

What is data governance?

Data governance is the practice that transforms an organization from simply having data to being truly data-centric. While technology supports it, governance is ultimately about people and process—putting the guardrails in place to mitigate risk while accelerating adoption.

Today, governance is viewed not just as a compliance necessity, but as a driver of revenue and business outcomes.

What are the benefits of data governance?

Good data governance first and foremost ensures the massive amounts of enterprise data in an organization can be harnessed for business value. Ungoverned data is messy, rule-less and cramps productivity. Data governance means an organization can trust their data to answer important questions, like which products in which markets are likely to deliver the highest revenue. Bad data means bad answers, which lead to bad decisions, which can hurt an organization fiercely.

Trust your data

When governance policies are defined and followed consistently, business users and customers can have more confidence in the accuracy of the data. A trusted data foundation helps improve collaboration between teams and ensures that analytics and AI functions are built on reliable inputs.

Improve productivity

Centralizing a data governance platform helps eliminate silos, which can reduce duplicate efforts and simplify access to critical data across an organization. Clear roles, workflows and policies reduce the time teams search for and manage data, leaving them freer to act on that information.

Make better decisions

The right data governance software supports business decision-makers by ensuring accurate, timely and well-documented data. By improving data quality and visibility, leaders are empowered to identify market trends quickly, better manage risk and drive business growth with greater confidence.

Keep up-to-date records

Strong data governance products help businesses monitor data and ensure the information they have is usable. Efforts, including version control and tools such as automated metadata tracking, help support current, relevant records for increased operational efficiency.

As an example, take a company with data inconsistencies. Say, customer names are listed differently in the systems where it resides, such as customer service, sales, or logistics systems. The lack of data governance means these issues aren’t resolved and the intelligence about customers will either be limited or plain wrong. A scary thought.

Maintain federal regulations

Federal regulations regarding data evolve constantly, particularly when it comes to emerging technology such as AI. From HIPAA to AI regulation, keeping up with these requirements can be daunting.Privacy laws, such as GDPR from the European Union, or CCPA from California, must be adhered to or regulators levy costly fines. Without data governance, an organization has no mechanism for seeing where an individual’s information exists and therefore has no way to remove or edit it to meet these regulations.

The right data governance frameworks offer audit, documentation and control tools that help companies meet federal regulations, reducing risks associated with fines or legal exposure.

Data governance helps with both defensive (avoiding fines and low productivity) and offensive (growth) use cases. Every sophisticated organization knows they need it to achieve the highest data benefits.

What are the goals of data governance?

Organizations implement data governance to achieve several critical objectives:

• Strategic maturity: Elevate the organization's data maturity to ensure all decisions are data-driven.
• Operational efficiency: Dismantle information silos, prevent duplication, and eliminate the time wasted on manual data massaging.
• Trust and quality: Guarantee data consistency and quality to build unwavering confidence in its trustworthiness.
• Risk and security: Establish robust security measures to prevent misuse and ensure all internal and third-party data remains safe and compliant.

Bottom line? Governed data removes operational friction and maximizes the value of your assets. If data isn't actively driving growth or reducing costs, it is a wasted resource. Governance bridges this gap, enabling you to move beyond gut instinct and achieve measurable results

How do you build a data governance framework?

A good data governance framework includes policies, procedures, processes, rules along with the right organizational structure and the technology to make it all happen. Believing a technology solution alone will magically result in success can be a fool’s errand. Any initiative is composed of people and processes, along with the supporting technology and data governance is no different.

The framework must also involve the executives in the organization. It has to be understood and appreciated in the boardroom or it will never survive at the troop level. Resources, in the form of both money and people, need to be allocated. Empowerment must happen. Leadership needs to lead and achieve alignment that ensures adoption.

Step 1: Define objectives

The first step of building the framework is to articulate the objectives in a Mission Statement and define the KPIs that will be used to determine progress. Expressing this early ensures that your effort is aligned with the vision.

Step 2: Set expectations

Then the framework must include all aspects of how the organization will govern its data. What are the rules? The policies? The processes and procedures? The business glossary? The map of all data assets? This step will consume significant energy, data experience, and knowledge of the organization.

Step 3: Determine accountability

Next, determine accountability. Who will be responsible for each part of the program, and who sits with overall responsibility and decision making?

Step 4: Choose a platform

Lastly, once the data governance framework is laid out, the committee will turn to technology and choose a platform that best supports the vision. A good technology solution will gather metadata from a variety of systems, manage a business glossary, enforce policies and procedures, tie to a technical data dictionary, and more. The ease of an integrated platform ensures these capabilities come together easily.

With all that in place, the realization of data governance in the organization can be achieved.

Learn more about Collibra’s Data Governance Solutions

What are the roles in a data governance framework?

Data governance is meant to enable collaboration; therefore, implementing a plan requires cross-functional collaboration. In order to set up an effective and scalable program, the data governance team needs to build a committee, bringing in stakeholders from across the organization to hold specific roles and responsibilities.

Line of business (LOB)

LOB can span many different departments, finance, marketing, analytics and more. LOB uses data everyday to support business decisions, so its role on the committee is to clarify how people are using data on any given day and what the data’s value is.

Data science

Data scientists want easy access to certified, trusted data, so they can quickly build and deploy models that contribute to higher quality analysis that ultimately drives the business forward. Similar to why the team needs to include the LOB, it is important to involve data scientists as daily users of data.

Privacy and compliance

This team owns all things related to data privacy and its goal to ensure regulatory compliance regarding the organization’s handling of personal data. This team’s role on the committee is to share its knowledge on how the organization can handle personal data under legal and regulatory constraints.

Information technology (IT)

Technology facilitates access to the data and adherence to rules and procedures. The IT team’s role is to help standardize workflows and monitor activities, ensure information security, and implement and deploy new technology if necessary.

Data governance

And of course, the data governance team’s role is to bring everyone together. The data governance team oversees the committee, defines processes, standardizes terms and strives to empower the rest of the organization around data.

What are data governance principles?

When building a data governance program, the committee should consider this set of principles:

Transparency

Transparency involves easy understanding of where data resides, what data is available and how people use the data. Data transparency is crucial for issues of privacy and security, especially considering growing scrutiny from regulators (i.e. the state of California and CCPA; the EU and GDPR) and awareness among the public (i.e. Equifax’s 2017 breach).

Accountability

Organizations need to endorse a culture of accountability around its data. Policies should make it clear that employees are fully answerable for how they handle data. Some ways to entrench accountability into the organization are:

• Assigning roles and responsibilities across the data lifecycle (i.e. who is responsible for creating data)
• Restricting access to sensitive data, so only those who need it to perform their jobs can access it
• Administering processes and procedures for
• Documenting how people use data, where it resides, and how it has moved or changed over time

Engagement

Data governance only makes an impact if all users adopt the best practices. It is essential to drive engagement from all stakeholders. In order to do this, the committee must understand data users’ needs and challenges and demonstrate why embedding data governance daily activities alleviates their problems. If users understand that it will actually make their lives easier, they will be more likely to support and adopt it. However, it is not enough just to tell them the benefits of data governance; the committee needs to implement an education and training program, so the users understand how to embed data governance into their daily activities.

Best Practices

A data governance program can feel overwhelming, but these best practices make it something every organization can achieve:

• Focus on the operating model
• Identify data domains
• Identify critical data elements within the data domains
• Define control measurements

Why data governance is crucial

Data governance has shifted from a back-office necessity to a frontline competitive advantage. Governance isn't just about policy; it's about decision velocity. Ensure your organization is built to win by turning your data into your most reliable strategic asset.

To learn more about Collibra Data Governance, visit our Product Page.

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  Meredith Bailey

  Meredith Bailey

  Senior Product Marketing Manager

  Collibra