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Greenstein, D.M. and Carter, B. (2023) Advances in Machine Learning for Business Decision-Making. Automated Machine Learning for Business Analytics.

has been cited by the following article:

• TITLE: Business Analytics in the Era of Big Data: Driving Informed Decision-Making

  AUTHORS: Md Ekramul Hoque, Bilkish Nurani, Niladry Chowdhury, Md Saidur Rahaman, Md Minhajul Amin

  KEYWORDS: Business Analytics, Decision-Making, Data Visualization, Predictive Analytics, Machine Learning, Big Data, Sector Adoption, Effectiveness of Tools

  JOURNAL NAME: Open Access Library Journal, Vol.12 No.1, January 31, 2025

  ABSTRACT: Business Analytics (BA) has become a transformative tool in driving data-informed decision-making across industries. This study explores the adoption rates, impact on decision-making, and the effectiveness of BA tools in diverse sectors, including finance, retail, healthcare, manufacturing, and telecommunications. It highlights key trends in BA adoption, analyzes its impact on decision-making processes, and evaluates the effectiveness of popular tools such as data visualization, predictive analytics, machine learning, and big data processing. Furthermore, it examines the reduction in decision-making time due to BA implementation. The findings indicate significant improvements in decision-making efficiency and effectiveness across all sectors, though the degree of adoption and impact varies. This paper provides actionable insights for organizations aiming to optimize their use of BA tools to achieve strategic objectives.