The Role of Data Science in Advancing Predictive Analytics and Decision-Making

Authors

  • Dr. Hassan Shahid Department of Computer Science, National University of Sciences and Technology (NUST), Islamabad, Pakistan. Author

DOI:

https://doi.org/10.71465/hjmri.311

Keywords:

Data Science, Predictive Analytics, Decision-Making, Machine Learning, Big Data, Predictive Modeling, Regression Analysis, Forecasting, Clustering, Data Integration

Abstract

Data science has emerged as a crucial field for advancing predictive analytics and enhancing decision-making processes across industries. This article explores the transformative role of data science in predictive modeling, machine learning algorithms, and big data analytics to improve decision-making accuracy in various sectors such as healthcare, finance, and retail. The evolution of data science tools has empowered organizations to use historical and real-time data to anticipate trends, optimize operations, and increase profitability. We discuss the application of data science techniques to predictive analytics, the challenges in data quality and integration, and the future trends that could revolutionize the decision-making landscape. This study highlights key methodologies, including regression analysis, time series forecasting, and clustering, in improving organizational decisions

image

Downloads

Published

2025-04-29

Issue

Vol. 5 No. 4 (2025): Holistic Journal of Multidisciplinary Research Innovation

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

All articles published in the Holistic Journal of Multidisciplinary Research Innovation are licensed under an open access model. Authors retain copyright of their work and grant the journal the right of first publication. The content may be freely used, distributed, and reproduced in any medium, provided the original work is properly cited and remains unaltered.