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What is data governance?

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This blog has been expertly reviewed by Andrea Rosales, Data Scientist at Colibri Digital. 

Modern businesses gather data at scale. From structured customer data to raw text, an organisation might see gigabytes or petabytes of new information being stored daily. With this data comes power and insights — but only if it’s stored, managed, and used correctly. That’s where data governance comes in. 

But what is data governance, and what does it mean for your business? A well-structured data governance strategy is vital to setting quality guidelines. It guides the way to making data genuinely valuable and trustworthy in business decision-making. It also helps ensure that all information is secure, stored correctly and shared with suitable stakeholders.  

This becomes even more critical as data privacy laws and regulatory requirements tighten. In this blog, we explore data governance, its advantages, and what a solid framework looks like. Then, we’ll look at best practices and the future of data governance in the cloud. Let’s get started. 

What does data governance mean? 

Andrea Rosales, Data Scientist at Colibri Digital, said: “Data governance helps to simplify data management within an organisation. Its primary goal is to make sure your data is not only accessible and secure but also in a format that everyone can trust. This involves having a clear understanding of who holds responsibility for various data assets, while ensuring accuracy, consistency, and security across data sources.” 

In this way, data governance builds a clear roadmap of data ownership. It considers things like:  

  • Accessibility 
  • Data lineage  
  • Compliance with regulations 

Andrea continued: “This makes it a cornerstone of modern business strategies. Metadata often supports the strategy, holding data definitions and information. It provides essential context about the data collected too, helping stakeholders learn the significance of data in terms of usefulness and origin.” 

Why data management is important 

So, why does putting effort into data governance matter? Well, data is only helpful if you actually use it. And you can only use it for important decisions if you trust it and have access to it when needed. 

Fundamentally, this is why data management is so important. A recent McKinsey report showed the negative impact of poor data governance. Among the respondents, almost one-third of employee time was wasted due to poor data governance. 

Implementing transparent data governance processes can help a company avoid the impact of poor data standards. Once in place, data management is the process of actioning the workflows set out by your data governance policy. This might sound like a somewhat daunting task — however, with proper planning, creating a data governance programme is straightforward. And the rewards are potentially enormous. 

What are the benefits of data governance? 

Proper data governance sets the foundation for many significant business advantages. 

Ensure data quality 

Data governance helps cement the quality, security, and usability of your data. Its processes and workflows are pivotal in maintaining data reliability and consistency. These checks help reduce costly inaccuracies, ensuring your decisions are based on solid, up-to-date information.  

Improve data security 

Security is another foundation of data governance. Not all information is for everyone's eyes. This is especially true of sensitive data, such as identifiable or financial records. By establishing access controls, data governance ensures that only authorised personnel can access sensitive information — safeguarding your organisation's confidentiality and protecting against breaches. 

Manage data flows 

A key challenge for modern businesses is integrating data from diverse sources. Data governance initiatives will dictate how to merge disparate information into one cohesive system. This step is vital for understanding business segments and making informed strategic decisions, especially if you’re using your data for advanced analytics. 

Prevent data misuse 

Data governance also plays a crucial role in preventing data misuse. By setting clear access and usage guidelines, organisations gain a deeper understanding of their data's reliability and relevance. This enables faster projects, proactive risk management, and more straightforward regulatory compliance. 

Cost reduction 

As data governance improves data quality, it also reduces data redundancy, error, and inefficiencies. This means organisations can optimise their resources to minimise any unnecessary expenses. Businesses can make informed decisions about how they store, archive, and delete their data to make cost savings associated with data lifecycle management. 

Transform data access 

Finally, the most significant business gains are made by making the correct data accessible to the right employees. By centralising data storage and simplifying its organisation, employees are empowered to use data effectively. This builds a data-driven culture where every team member understands the value of information, how it's collected and its role in driving the business forward. 

The types of data governance frameworks 

How organisations manage their data significantly impacts their success. A data governance framework is a blueprint for handling data, and understanding the type that suits your organisation is crucial. Data Governance outlines four main data governance frameworks: 

  1. Top-down: Spearheaded by company leadership, this approach sees policies made at the top and spread throughout the organisation. This ensures uniformity. However, it requires active and consistent leadership which can be time-consuming. 
  2. Bottom-up: This approach allows for the initiation of governance practices. For example, standardising naming conventions by lower-level employees would gradually influence the entire organisation. This requires solid guidelines and a clear hierarchy. 
  3. Centre-out: A dedicated data governance authority sets the standards that the entire organisation adopts, ensuring a centralised approach to data management. Many organisations find this appealing as an expert is dictating the terms — but it still requires everyone to be on board. 
  4. Silo-in: Departments collaborate to align data governance efforts. They tailor practices to meet specific group needs without losing sight of the organisation's objectives. While this makes for compelling decision-making, the group must have trust and authority. 

While these frameworks offer a good starting point, it’s possible to make tweaks where needed. Some businesses might find a hybrid model more fitting, blending these approaches to suit their unique requirements. The choice of framework influences how effectively data governance can support the organisation's goals. 

Data governance best practices 

A solid data governance model usually combines three primary factors: Processes, policies, and roles and responsibilities. Together, these aim to make data accessible, understandable, secure, high-quality, and well-integrated.  

  • Policies provide documented rules and guidelines for data management 
  • Processes outline the steps needed to manage and govern data effectively 
  • Roles and responsibilities assign tasks to individuals or teams, clarifying who is accountable for what 

Usually, it’s best to start small and focus on specific tasks or workflows. For instance, you could start with one data source, one outcome, or one team in mind. Then, build a data governance framework that supports them in getting the most out of their information. Once this successful proof of concept is in place, you can scale this to meet your other digital transformation efforts. 

Who should own data governance processes? 

Data governance is a collaborative effort that ensures data within an organisation is managed with due care. But for it to be effective, a broad range of roles must be involved. This covers day-to-day operational staff and system admins through to management. 

We can define three distinct roles within this effort, each with different responsibilities: 

  1. Data owners: These individuals take responsibility for the strategic direction, quality, and policy guidance of specific datasets. Their role ensures the data serves the organisation's long-term goals and meets quality standards. 
  2. Data architects: Architects design and implement the overall structure and architecture of data systems and databases. Their participation and guidance in data storage, consumption, integration, and management is crucial when building a data governance programme. 
  3. Data stewards: The stewards are the hands-on managers of data. They uphold daily governance policies and monitor things like regulatory compliance. Above all, they act as the custodians, ensuring data is appropriately used and kept in prime condition. 
  4. Data consumers: The consumers use data in their daily tasks. While not involved on a technical level, their feedback is crucial for understanding the data's utility and identifying areas for improvement. 

For data governance to truly succeed, each level must play its part. Together, they form a unit where data is owned, managed, and embraced. 

Cloud data governance 

Cloud data governance is the strategic framework organisations use to manage their data within cloud environments. As companies increasingly turn to cloud solutions for scalability, flexibility, and cost benefits, data governance ensures data remains secure, accessible, and in compliance with both internal policies and external regulations. 

Often, the framework and ownership policies are similar to on-premise data sources. Implementing robust cloud data governance is crucial for any organisation looking to harness the full potential of cloud computing while safeguarding its data against breaches, loss, or misuse. 

How Nasstar and Colibri Digital can help 

Data governance is the strategic oversight of an organisation's data quality, accessibility, consistency, and security. It involves a set of policies, processes, and roles to ensure data is reliable, secure, and used effectively.  

With the increasing reliance on data for decision-making and compliance with regulatory requirements, effective data governance is crucial. It enables organisations to improve decision quality through maintaining trustworthy and secure data sources. By establishing clear frameworks and responsibilities, data governance supports future business objectives. 

Nasstar cloud services and Colibri Digital’s data expertise can help you begin your data governance framework. From data governance tools to data quality guidelines, our expert team can help you achieve compliance, data security, and informed business decisions.  

Speak to a specialist to learn more. 

Frequently Asked Questions (FAQs) 

What is data governance with an example? 

Data governance is the framework for guarding and using an organisation's information assets. Among other things, it aims to ensure data quality, security, and integrity. For example, a chain of shops might have data governance in place to maintain inventory and customer information across multiple sites.  

Proper data governance involves setting policies for how data is collected, stored, and accessed. The aim is to make data trustworthy, secure, and reliable for business intelligence, as well as meet regulatory requirements. 

Who is responsible for data governance? 

Responsibility for data governance is spread across an entire organisation. It involves everyone — from the boardroom down to the day-to-day operational level. However, there are specific essential roles to be undertaken.  

Data owners oversee strategic decisions and direction. Data stewards ensure day-to-day policy implementation and compliance. Data consumers use the data in their roles and feedback on any issues. Effective governance requires collaboration across these roles, integrating data management into every part of the business. 

Is data governance part of cyber security? 

Data governance is a vital component of cyber security. It includes the policies and procedures that protect enterprise data from unauthorised access or breaches — playing a crucial role in the overall security posture.  

Specifically, by defining who and when can access data and how data integrity is maintained, data governance supports cyber security efforts. Overall, both aim to safeguard sensitive information and ensure compliance with data protection needs.