What is Data Governance?

The growth of data has never been greater in terms of variety, volume and velocity, and this applies to both operational and informational data and advanced analytics. The number of companies with more than 100 TB of unstructured data has doubled since 2016. Data sources have multiplied with social networks, mobile applications and data sensors.

Within organisations, data is increasingly present, used and shared, and access to it is democratised. However, we are seeing more and more cyber-security breaches and data fraud, and sometimes poor decisions are being made because of poor-quality data.

Not to mention the fact that regulatory bodies are specifying and increasing standards and regulations, particularly on personal and confidential data, to ensure that it is managed with the utmost security. That's why good data governance has become essential.

Definition of Data Governance

Data governance is a set of processes, strategies, roles and standards designed to ensure that information is used reliably and securely. It provides a framework for managing data throughout its lifecycle so that it remains accurate, private, accessible and usable. In other words, it ensures that data circulates within the organisation in a coherent, controlled and secure manner.

Putting in place a robust data governance strategy has become essential for organisations that want to drive growth, strengthen strategic decisions and achieve their objectives in an increasingly competitive marketplace. By collecting large volumes of internal and external data, businesses need to establish a framework for reducing risk, controlling costs and transforming information into real business value.

The Benefits of Data Governance

Improving data quality

Effective governance ensures that data is reliable, consistent and error-free. It eliminates duplication, corrects inconsistencies and ensures that the information used for analysis and decision-making is always accurate.

Regulatory compliance

The rules and regulations governing the protection and confidentiality of personal data are increasing considerably as access to data becomes more widespread and the amount of information available increases.

There are a number of laws governing data management. Here is an overview:

• In Quebec, Bill 64 (PL-64) includes the obligation for all businesses to establish and implement policies and practices framing their data governance with regard to personal information. Companies must publish these policies on their website.

• In Canada, Bill C-11 is a reform currently being formalised with the scope of personal information and data protection.

• In Europe, there is already in place, the RGPD or General Data Protection Regulation.

Improved decision-making

Well-governed data provides a solid basis for strategic and operational decision-making. Managers and executives can rely on accurate, up-to-date information to anticipate trends, optimise processes and adjust their strategies.

Enhanced security

Governance establishes clear rules on who can access what data and under what conditions. By limiting access and ensuring traceability, it helps to prevent security breaches, fraud and unauthorised use.

Increased efficiency

Finally, well-structured governance helps to optimise the use of data, reduce redundancies and streamline internal processes. The result: greater productivity, lower costs and a greater ability to exploit the full potential of its information assets.

How do you set up a data governance strategy?

Implementing a data governance strategy is a structuring project that requires commitment and a clear vision. It is not limited to technological tools: it is a global approach that involves the organisation's management, teams and processes.

1. Obtain executive sponsorship

Successful governance requires the involvement of senior management. Without executive commitment, it is difficult to establish a culture of responsible data management. Executive support makes it possible to mobilise the necessary resources, legitimise the rules put in place and ensure that they are adopted at all levels.

2. Mapping the data

Once the project has been launched, it is essential to identify and document existing data, its sources and flows. This mapping makes it possible to know where the data is, how it flows and who has access to it. It forms the basis of sound governance, providing a clear view of the company's information assets.

3. Defining rules and policies

Governance must then be based on well-defined internal policies: how to collect data, where to store it, how long to keep it and under what conditions to share it. These policies must be aligned with legislation (e.g. Law 25, RGPD) and adapted to the company's operational realities.

4. Establish roles and responsibilities

Success is based on the appointment of data stewards and a chief data officer (CDO. These players monitor governance on a daily basis, raise awareness among employees, and ensure that the rules are complied with. They act as intermediaries between the IT teams, the business lines and management.

5. Measuring progress

Finally, an effective strategy must include performance indicators: data quality (error rates, completeness), regulatory compliance, information access times, security incidents. Monitoring and continuous improvement ensure that governance evolves with the needs of the organisation and new regulations.

Data Governance Tools

Data governance is not only based on policies and roles: it also relies on technological tools that facilitate the concrete application of rules, the classification of information and the continuous monitoring of its use. These solutions make it possible to automate part of the work and reduce the risks associated with human error.

Cataloguing and classifying data

Cataloguing tools help to identify, organise and categorise company data. They make it possible to know where sensitive data is located, define clear metadata and make it easier for authorised users to find it. Automatic classification (for example, according to the type of personal or financial data) is a major asset in ensuring compliance and traceability.

Security and access control

Another aspect is the management of rights and access. Governance solutions make it possible to define who can consult, modify or share specific data. This reduces the risk of information leaks and protects confidential data through mechanisms such as enhanced authentication, encryption or anonymisation.

Monitoring and regulatory compliance

Modern platforms incorporate real-time monitoring functionalities: alerts in the event of non-compliant use, automated reports to demonstrate compliance with legislation, and monitoring of retention obligations. This facilitates audits and reduces the risk of sanctions.

Examples of tools used by organisations

• Microsoft Purview (ex-Azure Purview): offers a unified data catalogue, classification of sensitive data and tracking of its traceability (data lineage).

• Talend Data Fabric: combines data integration, quality and governance in a single platform.

• SAP Master Data Governance (MDG): specialising in the centralised management and quality of master data.

• Google Cloud Data Governance: focused on the security, privacy and visibility of multi-cloud data.

These tools do not replace a strategy, but reinforce it and enable organisations to move from theoretical policies to concrete, measurable application of data governance.