Big Data and Business Analytics: Foundations, Methods, and Strategic Applications
Keywords:
big data, business analytics, data mining, predictive analytics, data visualisation, machine learning, decision-making, and data governance.Abstract
Big data and business analytics are transforming modern organisations, allowing them to make data-driven decisions and gain strategic advantages. This essay will cover the notion of big data, defined by its volume, velocity, and variety, and how sophisticated analytics approaches may translate intricate datasets into valuable insights. It emphasises the significance of business analytics (descriptive, predictive, and prescriptive) for improving operational efficiency, customer experience, and competitive positioning. The article further examines the main technologies, challenges such as data privacy and integration and the growing role of data governance. To illustrate the value of big data and analytics in the real world, the article explores applications in several industries that demonstrate how organisations may harness these tools to innovate, optimise performance, and achieve sustainable growth in a rapidly digitising environment.
How to cite this article:
Hans V B. Big Data and Business Analytics: Foundations, Methods, and Strategic Applications. J Adv Res Qual Control Mgmt 2026; 11(2): 35-43.
DOI:https://doi.org/10.24321/2582.3280.2026010
References
Hassan Zadeh A, Schiller S, Duffy K, Williams J. Big Data and The Commoditisation of Analytics: Engaging First Year Business Students with Analytics. 2018. e-Journal of Business Education and Scholarship of Teaching Vol. 12, No. 1, 2018, pp. 120-137. “http://www.ejbest.org/
Alharthi M. The Role of Big Data in Strategic Decision Making for Organisations: A Review. 2018. www.informs.org/
Vera-Baquero, A., Colomo-Palacios, R., Molloy, O., Elbattah, M. Big Data based Decision Support Systems for business process improvement: a case study on Call Centers. 2015. February 2022International Journal of Information Systems and Project Management 3(1):5-26 DOI:10.12821/ijispm030101
Zlatev V, Ivanov P. Methodological framework of applied business analytics approach to IT projects. 2017. https://open.bu.edu/
Iqbal M, Kazmi SA, Manzoor DA, Soomrani RA et al. A Big Data Study for Business Growth in SMEs: Opportunities & Challenges. 2018. DOI:10.1109/ICOMET.2018.8346368 Conference: International Conference on Computing, Mathematics and Engineering Technologies (iCoMET), 2018
A Review Paper on Big Data Management. Kaustubh D M, Vikash Singh M, Madhur Ahuja M, Gaganjot Kaur M. 2019. Journal of Data Mining and Management e-ISSN: 2456-9437 Volume 4 Issue 1 32
Verbitskiy, Y., & Yeoh, W. (2007). Data quality management in a business intelligence environment: The metadata perspective. 2011. https://www.researchgate.net
Anstiss, Sarah and Marjanovic, Olivera, "Understanding Data Quality Issues in Dynamic Organisational Environments : A Literature Review" (2012). ACIS 2012 Proceedings. 35. https://aisel.aisnet.org/acis2012/35
Rossi R, Hirama K. Towards a Conceptual Approach of Analytical Engineering for Big Data. 2022. The paper can be found here: https://arxiv.org/abs/2201.05754
Richly, Marc A. (2022) : Big Data Analytics Capabilities: A Systematic Literature Review on Necessary Skills to Succeed in Big Data Analytics, Junior Management Science (JUMS), ISSN 2942-1861, Junior Management Science e. V., Planegg, Vol. 7, Iss. 5, pp. 1224-1241, https://doi.org/10.5282/jums/v7i5pp1224-1241
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