Contextual Data Quality Management within Enterprise Architecture Frameworks[Gestion de la Qualité des Données Contextuelles dans les Cadres d'Architecture d'Entreprise]

In the era where data-driven decision-making is essential, maintaining high data quality and robust data management practices within Enterprise Architecture (EA) is a priority, where EA serves as a blueprint that integrates data quality and data management into organizational processes. In our thesis we aim to improve data quality within EA layers using Machine Learning. Embedding Machine Learning into EA components enhances data quality, automates data management processes, and provides predictive insights, optimizing decision making and aligning data governance with organizational objectives. Our research is focused on a real estate organization where the implementation and maintenance of optimal data quality and effective data management practices present significant challenges.