FACT-DM : A Framework for Automated Cost-Based Data Model Transformation [EDBT’24 & BDA’24]

As data continues to grow at an unprecedented rate, the complexity of database systems also increase significantly, requiring Information Systems (IS) architects to constantly adapt their data model and carefully select the optimal solution(s) for storing and managing data that align with new queries, settings, and constraints. Having a tool to visually show the impact of different changes, will help IS architects in their decision making. In this paper, we propose a framework to demonstrate the impact of denormalization of data models on their cost and consequently IS architects can choose the best trade-off.

This work has been developed by Jihane Mali, my former PhD student (defended in August 2024). She was co-advised by Shohreh Ahvar (Nokia, formerly ISEP), Faten Atigui (CNAM), Ahmed Azough (ESILV) and myself.

Complementary works have been submitted to Information Systems Journal (IS) where we demonstrate our Cost Model focused on Environmental Footprint of data models on the Cloud, and a stability optimisation of data models.