Data science maturity model: from raw data to pearl’s causality hierarchy

Cavique, Luís; Pinheiro, Paulo; Mendes, Armando B.

http://hdl.handle.net/10400.2/20354

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Autores

Cavique, Luís

Pinheiro, Paulo

Mendes, Armando B.

Resumo(s)

Data 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.

Palavras-chave

Data science Maturity models Business experimentation Wh-questions Causality

URI

http://hdl.handle.net/10400.2/20354

Citação

Cavique, 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_32

DOI

10.1007/978-3-031-45648-0_32

Coleções

Ciências e Tecnologia | Comunicações em congressos, conferências, seminários/Communications in congresses, conferences, seminars

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