Resumo
This article aims to address the topic of data analysis, providing a comprehensive overview of the concept, techniques, and methods of utilization, as well as examples of possible applications. Although the field of Data Science is relevant to companies and businesses of all sizes, this article will focus its efforts on highlighting the specific importance and relevance of this discipline for small businesses. In this regard, an accessible and easily understandable language will be explored, with the intention of simplifying the methods of application and facilitating the assimilation of this knowledge by entrepreneurs and managers of small businesses. Practical examples of how data analysis can be implemented in different areas such as marketing, sales, operations, and strategic decision-making will be addressed. Additionally, the direct and indirect benefits that small businesses can obtain by adopting a data-driven approach will be discussed.
Referências
COELHO, Lucas. Ciência de Dados: O que é, Conceito e Definição. Disponível em: https://www.cetax.com.br/blog/data-science-ou-ciencia-de-dados/. Acesso em: 28 abr. 2023.
DHAR, Vasant. Data science and prediction. Communications of the ACM, v. 56, n. 12, p. 64-73, 2013.
FURLAN, Marco R.; FILHO, Educaro V. G. Uma proposta de aplicação de business intelligence no chão-de-fábrica. Gestão & Produção, v. 12, n. 1, p. 55-66, jan.-abr. 2005.
KELLEHER, John D.; TIERNEY, Brendan. Data Science: An Introduction. 2018.
MANYIKA, J. et al. Big data: The next frontier for innovation, competition, and productivity.McKinsey & Company: McKinsey Global Institute, 2011.
PROVOST, Foster; FAWCETT, Tom. Data Science for Business: What you need to know about data mining and data-analytic thinking. “ O’Reilly Media, Inc.”, 2013.
SEMPLE, Kirk. Data Science Is Changing How Nuts.com Runs Its Business. Forbes, 20 jun. 2016.
YIN, Robert. Case Study Research: design and methods . 5 ed. Thousand Oaks, CA: Sage , 2014.