FROM DATA TO DEVELOPMENT: LINKING BDA TO MANAGEMENT SKILL ACQUISITION IN THE ERA OF BIG DATA

Authors

  • Muhammad Hiyat Department of Computer Science,The University of Hertfordshire (UH), United Kingdom(UK).
  • Muhammad Tanveer Meeran Faculty of Computer Science and Mathematics, Universiti Malaysia Terengganu, Malaysia.
  • Salahuddin Department of Computer Science, NFC Institute of Engineering and technology, Multan, Pakistan.
  • Bareerah Saeed Department of Computer Science, COMSATS University Islamabad, Vehari Campus.
  • Aysha Rashid Department of Computer Science, COMSATS University Islamabad, Vehari Campus.
  • Muhammad Ramzan Department of Computer Science , Islamia University of Bahwalpur.

Keywords:

Big data Analytics, Talent Management and Artificial Intelligence

Abstract

The business world increasingly relies on big data to enhance organizational performance and decision-making. This shift is now fundamentally transforming the Human Resources (HR) sector. Traditionally, HR has grappled with measuring intangible elements like employee attitude and behavior. This article explores how Big Data Analytics (BDA) can be leveraged to address this challenge, linking it to the development of critical management skills such as intelligence, drive, strategic thinking, and ethics. By applying predictive analytics and data-driven insights, HR departments can move beyond traditional metrics to foster a more innovative and effective leadership culture. This research posits that the integration of BDA is not merely a technological upgrade but a strategic imperative for building future-ready organizations. Using quantitative analysis, this study employs a self-developed survey and SPSS to measure BDA's impact across the full spectrum of management skills within an HR context.

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Published

2025-09-30

How to Cite

Muhammad Hiyat, Muhammad Tanveer Meeran, Salahuddin, Bareerah Saeed, Aysha Rashid, & Muhammad Ramzan. (2025). FROM DATA TO DEVELOPMENT: LINKING BDA TO MANAGEMENT SKILL ACQUISITION IN THE ERA OF BIG DATA. Spectrum of Engineering Sciences, 3(9), 1464–1477. Retrieved from https://thesesjournal.com/index.php/1/article/view/1132