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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM63111
Volume:
10 |
5 |
May 2026
Pages:
1-3
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Master Computer Application
G H Raisoni College of Engineering and Management Wagholi, Pune, India
Master Computer Application
G H Raisoni College of Engineering and Management Wagholi, Pune, India
Master Computer Application
G H Raisoni College of Engineering and Management Wagholi, Pune, India
Master Computer Application
G H Raisoni College of Engineering and Management Wagholi, Pune, India
In the modern business environment, organizations generate large amounts of data from daily operations, customer interactions, and digital platforms. Analyzing this data effectively has become essential for making accurate and strategic business decisions. Data science provides advanced techniques such as data analysis, statistical modelling, and machine learning to transform raw data into meaningful insights. This research explores the role of data science in improving business decision making by identifying patterns, predicting future trends, and supporting data-driven strategies. The proposed approach focuses on collecting business data, processing it using analytical methods, and presenting insights through visualization tools. These insights help managers understand market behaviour, customer preferences, and operational performance. The study shows that organizations using data science techniques can improve efficiency, reduce risks, and make more informed decisions.
KEYWORDS
Data science plays a very important role in modern business environments. It helps organizations analyse large amounts of data and convert it into useful information that supports better decision making. Tools and methods such as data analysis, machine learning, and predictive models allow businesses to make informed decisions based on real data instead of assumptions. This helps organizations improve productivity, reduce business risks, and make better strategic plans. As a result, companies can achieve higher efficiency and maintain a strong position in the competitive market. Even though there are some challenges like maintaining data quality, protecting data privacy, and the cost of implementing advanced technologies, the advantages of data-driven decision making are much greater.
[1] D. J. Patil and H. Mason, Data Driven: Creating a Data Culture. Sebastopol, CA: O’Reilly Media, 2015. Link: https://www.oreilly.com/library/view/data-driven/9781491916902/ [2] McKinsey Global Institute, Big Data: The Next Frontier for Innovation, Competition, and Productivity. [Online]. Available: https://www.mckinsey.com/capabilities/quantumblack/our-insights/big-data-the-next-frontier-for-innovation [3] IBM Corporation, What is Data Science? [Online].Available: https://www.ibm.com/topics/data-science [4] F. Provost and T. Fawcett, Data Science for Business. Sebastopol, CA: O’Reilly Media, 2013. Link: https://www.oreilly.com/library/view/data-science-for/9781449374273/ [5] T. H. Davenport and D. J. Patil, “Data Scientist: The Sexiest Job of the 21st Century,” Harvard Business Review, 2012. Link: https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century
Publication Date
5/12/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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