The Role and Applications of Data Science in Modern Business

Businesses generate vast amounts of data through customer interactions, daily operations, supply chains, and digital platforms. Data science—the integration of statistical methods, computational techniques, and domain knowledge to extract actionable insights from data—has become increasingly important to contemporary business. It helps organizations inform strategic decisions, improve operational efficiency, and strengthen customer relationships. This paper examines the applications and organizational effects of data science, focusing on predictive analytics, machine learning, customer segmentation, and big data management. It considers how these methods are used in marketing, supply chain management, finance, and customer service, alongside the tools and technologies that support their adoption. The review also addresses key benefits and challenges, including data quality, shortages of skilled professionals, privacy concerns, and infrastructure costs. Finally, it considers emerging developments in artificial intelligence, ethical data use, and the integration of data science into organizational practices. It argues that realizing the value of data science requires more than advanced algorithms: organizations must also align their people, processes, and expectations with their analytical goals.

Authors

Publication Details

Journal
International Journal of Innovative Science and Research Technology (IJISRT)
Published
2026-10-26
DOI
https://doi.org/10.38124/ijisrt/26oct892
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
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article

The Role and Applications of Data Science in Modern Business

Supriya Rajkumar Saw
International Journal of Innovative Science and Research Technology (IJISRT)
Big Data and Business Intelligence
article

The Role and Applications of Data Science in Modern Business

Supriya Rajkumar Saw
article en

Abstract

Businesses generate vast amounts of data through customer interactions, daily operations, supply chains, and digital platforms. Data science—the integration of statistical methods, computational techniques, and domain knowledge to extract actionable insights from data—has become increasingly important to contemporary business. It helps organizations inform strategic decisions, improve operational efficiency, and strengthen customer relationships. This paper examines the applications and organizational effects of data science, focusing on predictive analytics, machine learning, customer segmentation, and big data management. It considers how these methods are used in marketing, supply chain management, finance, and customer service, alongside the tools and technologies that support their adoption. The review also addresses key benefits and challenges, including data quality, shortages of skilled professionals, privacy concerns, and infrastructure costs. Finally, it considers emerging developments in artificial intelligence, ethical data use, and the integration of data science into organizational practices. It argues that realizing the value of data science requires more than advanced algorithms: organizations must also align their people, processes, and expectations with their analytical goals.

International Journal of Innovative Science and Research Technology (IJISRT)Vol. 11(10)
Openalex Percentile: Top 7%
Big Data and Business Intelligence
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The Role and Applications of Data Science in Modern Business — Supriya Rajkumar Saw · International Journal of Innovative Science and Research Technology (IJISRT) (2026) | TGRS Research Map | TGRS