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Data governance has become a essential approach for any company, at a time when Big Data is taking an important place in business models. This concept allows each organisation to manage your data for the purpose of make the most of it. Mastering this concept is essential to the success of a data governance project.

Data governance: definition

Data governance, translated as data governance, is the set of processes and rules that govern the collection, management and protection of a company's data. It involves establishing an internal framework for optimising the use of data, while complying with legal regulations such as the RGPD. Data governance applies to all the different departments of the company and ensures that data are consistent and accessible to the right people.

What are the challenges of data governance in business? 

Every organisation deals with a huge and growing amount of information. All this data is valuable, provided that identify reliable data and quality. In this sense, data governance plays a very important role. By adopting this approach, the company is able to make efficient use of large volumes of data in order to gain a competitive advantage.

One of the other issues of data governance concerns the protection of data. Processing a large amount of data is a complex task that requires compliance with specific rules. Within each process, all data must be compliant with regulations in force. With data governance, data protection becomes a standard. It enables the company to comply with the new regulations on personal data and to minimise the risks.

Data governance is also the driving force behind the digital transformation within a company. By making reliable data available, it enables each department to make informed decisions. ⁣ the best business decisions.

What are the areas of application of data governance ?

As the use of data grows, data governance is being applied to business processes in a variety of industries and is tending to be applied even more widely. Here are some examples :

• The medical sector The health sector is a highly regulated sector with regard to patient information and personal data. Data governance plays a crucial role in this sensitive area of business to protect data from misuse and unauthorised access.

• The risk management : Data analysis must be properly managed in order for managers to make effective decisions.
• The bank: data governance guarantees the protection of users and the smooth running of transactions.

The data governance approach also makes sense for companies in the context of mergers and acquisitions, as well as in the context of the possible application to machine learning and other AI tools.

What are the steps for a successful data governance project? 

The first step is to identify key data, necessary for a company's business challenges. By defining the data (date of origin, lifespan, etc.) and its uses, data governance makes it possible to share a common base and language to all employees. This data mapping facilitates access to information: everyone knows where to find the data, how it is used or transformed, and by whom.

In order to move towards a new data governance organisation, it is important to define the role of each person and the new responsibilities for data managers. This approach also requires passing on the data culture to all services to ensure that the facilitate the dissemination of information between all employees. In order to enhance the value of the data governance approach, it is necessary to put in place the appropriate IT tools for decision support and reporting, such as CRM, ERP, MDM, andprovide training for all levels.

Data governance professions

In order to succeed in a data governance project, it is essential to set up positions specifically for data management. Here are some of them:

• The chief data officer (CDO) is implementing the data governance strategy within a company. He leads the change management and ensures that all data is protected and provided to employees.
• The data protection officer ensures safety, the data privacy and compliance. It ensures that the data governance policy complies with current regulations.
• The data analyst operates and interprets the data to guide the decision-making process.
• The data scientist ensures theintegrity of the data, so that they can be properly exploited. They must be complete and of good quality.
• The data architectconceives the technical structure to collect, store and process data in a common database.

How to learn about data governance ?

To access the various data governance professions, ��ɫ��Ƶ offers various Master of Science programmes. The MSc Digital Marketing & Data Analysis provides a solid foundation in digital strategy development, data analysis, as well as a mastery of the challenges of individual data protection. The MSc Manager of digital transformation aims to train future managers capable of designing and to drive digital transformation within an organisation.