Data governance

Data governance involves defining the organisational constituents and their roles and responsibilities to ensure that each piece of data is owned and managed accurately and consistently, in line with the company's strategy.

Data architecture identifies and models the various components involved in storing, integrating, using, accessing and sending data across the enterprise.

Data retention and archiving helps to retain and archive data, both online and offline, while complying with regulatory, operational and information requirements.

Data quality management establishes a perimeter and appropriate processes for assessing quality problems, remedying them and measuring their evolution.

Metadata makes it easier to share, retrieve and understand data. This is made possible by documenting the business, technical, operational and organisational information for each piece of data (e.g.: definition, use, responsibilities, etc.).

Reference data management ensures data harmonisation and integrity throughout the company.

Data confidentiality focuses on compliance with internal and regulatory data confidentiality rules. Particular attention must be paid to all personal data.