What is data governance and why is it relevant for companies?

Data Governance is the set of policies, procedures, standards and practices established by companies to manage and protect its data. This practice aims to ensure that data is correct, consistent, secure, and available.

It is relevant to companies for several reasons:

1. Regulatory compliance: governments and laws have established regulations to protect user data and sensitive company data. It also helps to ensure that the company complies with these regulations and laws.
2. More accurate decision-making: Data is an important decision-making tool for any company. Data Governance helps to ensure that data has greater accuracy and reliability, thus making data-driven decisions more effective.
3. Improved efficiency: Efficient and standardised data management processes can help reduce errors and redundancies, improve productivity, and reduce costs.
4. Business growth: Access to accurate and reliable data can help identify business opportunities and foster growth.

In short, data governance is important to ensure the integrity, privacy and security of enterprise data and to help ensure its effectiveness and efficiency in a company’s decision-making.

A data governance expert must understand that data belongs to people and that collaboration is crucial to success. To foster collaboration, companies must recognise the importance of data and assign people to roles responsible for data quality, access and management.

In addition, it is essential to involve all business lines and levels within the company, and to convey the value of data governance so that data is easier to find, understand and trust. Also, it is important to recognise the disconnect between IT and the business (in terms of real business needs), address data management issues, and work to break down data silos.

Finally, data governance experts must understand that technology must be strategic, and that the entire data ecosystem must be transparent to all departments and business units. Implementing appropriate technologies and not simply storing data centrally is essential to successful data governance.

Let's examine these actions in detail:

• Importante of data

First, it is important to recognise that data are much more than records, fields and tables. Obtaining quality data requires the involvement of the individuals responsible for management, access and quality. It is essential to have a clear vision of the importance of data in order to properly address its management and leverage its potential.

• If the data are important, the owners are even more so

It is crucial to identify those individuals skilled in data management who will serve as effective data administrators. These ideal owners should have the relevant business expertise and a passion for attention to detail. These are the people in the company who always know the location and meaning of the data and have become great ambassadors. A company must be cognizant of how changes will affect the business units and then incorporate this knowledge into the processes that are built.

• Not everyone is an expert in data governance

Once leaders and stakeholders are engaged, it is important to have a data governance expert involved at all levels of the business, as the business owns the process. The aim of data governance is not simply to have flawless data, but to help people use it with confidence in the achievement of business objectives. It is necessary to build trust in the data and make the data available to everyone in the organisation. Therefore, it is necessary to have a data governance expert in place who works with all levels and business lines within the company to ensure effective data governance.

• Enhancing the value of data governance

It is important to highlight the value that data governance brings to the organisation. Implementing good governance practices makes it easier to find, understand and trust data. As such, users must be involved in the process and must prioritise what information they need and who can access it. By focusing on critical data elements, IT can ensure data availability and ease of access for users.

• Streamlining data use

While business users value data for its utility, IT sees all data as the same. This leads to frustrations on the user side when data is expressed in technical terms and on the IT side when data is not used despite the cost of implementation. It is recommended that companies take small steps to break down these silos, address data management issues and agree to share data, without limiting data governance efforts. It is also important to pay attention to other data projects and working groups and demonstrate how governance addresses the challenges identified.

• Data management technology cannot be overlooked

A data governance specialist recognises the importance of looking at technology from a strategic perspective and not just a means of storing data in one place. This approach, which has driven data warehouse projects for more than a decade, has largely failed. Data is known to be stored in multiple systems across the organisation and this is unlikely to change. Ultimately, the entire data ecosystem needs to be transparent to all departments and business units to achieve true data management efficiency. The trend towards cloudification is changing this perspective, as in some ways it makes it easier to interconnect information and access it as an authorised user.

And technology is exactly where we can find a great ally for data governance, thanks to the availability of specialised software that provides significant help for those involved in data projects within the organisation.

Data governance software is a technological tool that helps companies manage and control their data efficiently and securely. Some of its main functions are described below:

1. Data classification: makes it possible to identify and label the different types of data processed by the company, facilitating its management and control.
2. Access control: allows data access permissions to be defined and managed according to roles and responsibilities of users within the organisation.
3. Regulatory compliance: Helps ensure compliance with rules and regulations related to personal data protection, information security and privacy.
4. Data quality management: Facilitates the definition of rules and quality standards for data and monitoring their compliance through automated checks and corrections.
5. Data monitoring: Provides real-time information on data usage and quality to aid decision-making and identifying problems.
6. Risk management: Enables identification and mitigation of risks associated with data management, such as data loss, regulatory non-compliance and exposure of sensitive data.
7. Collaboration and communication: Encourages collaboration and communication between the different departments and teams involved in data management, thus improving data management efficiency and effectiveness.

In short, data governance software is an essential tool for companies that want to manage their data effectively, ensure its security and privacy, and comply with applicable rules and regulations.

And when we talk about regulatory compliance, international standards apply, in particular European regulations, such as the GDPR, which we will discuss in more detail in the next article.