Companies today have several major issues while managing information. Many subsidiaries and departments have developed their own Data Management which has led to a multitude of Operational Databases and sometimes a multitude of Data Marts, policies and processes. Thus, these systems lack sustainability because they are not dynamic and not self-organizing, and so they do not adapt to the continuous needs arising from evolution that the companies experience. The Dynamic Data Mart architecture is built around 6 main functions, namely the 3Ms (Data Mining, Data Marshalling and Data Meshing) and the 3Rs (Recommendation, Reconciliation and Representation), which will address the aforementioned problems. Once the totality of the data have been loaded into a single Data Warehouse, the Dynamics Data Marts address these problems by mining the user’s behavior and the user’s decision making processes and continuously and automatically adapting the Data Mart to the needs of the users. Dynamic Data Marts create adapted dimensions, facts, data associations and views and then automatically find the ones that are not used anymore. These latter are then automatically dropped by the system, or can be presented to the IT manager if needed for validation of their removal.