Cavique, LuísPinheiro, PauloMendes, Armando B.2025-10-142025-10-142024-02-18Cavique, L., Pinheiro, P., Mendes, A. (2024). Data Science Maturity Model: From Raw Data to Pearl’s Causality Hierarchy. In: Rocha, A., Adeli, H., Dzemyda, G., Moreira, F., Colla, V. (eds) Information Systems and Technologies. WorldCIST 2023. Lecture Notes in Networks and Systems, vol 801. Springer, Cham. https://doi.org/10.1007/978-3-031-45648-0_32978-3-031-45647-3http://hdl.handle.net/10400.2/20354Data maturity models are an important and current topic since they allow organizations to plan their medium and long-term goals. However, most maturity models do not follow what is done in digital technologies regarding experimentation. Data Science appears in the literature related to Business Intelligence (BI) and Business Analytics (BA). This work presents a new data science maturity model that combines previous ones with the emerging Business Experimentation (BE) and causality concepts. In this work, each level is identified with a specific function. For each level, the techniques are introduced and associated with meaningful wh-questions.We demonstrate the maturity model by presenting two case studies.engData scienceMaturity modelsBusiness experimentationWh-questionsCausalityconference object10.1007/978-3-031-45648-0_32