International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 11 | Nov 2025
p-ISSN: 2395-0072
www.irjet.net
Big Data Analytics in E-Commerce: A Comprehensive Literature Review SRAVAN K M MSc Computer Science Student, St. Thomas (Autonomous) College, Thrissur 680001, Kerala, India
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Abstract - An exponential rise in data generation, driven by
literature, covering the evolution and core definitions of BDA, its thematic applications, and the prevalent methodologies. Section III offers a critical analysis of the findings and identifies pertinent research gaps. Section IV elaborates on diverse applications and relevant case studies. Section V discusses the inherent challenges and proposes future research directions, while Section VI concludes by synthesizing the knowledge and highlighting business implications.
the spread of internet technologies, establishes Big Data Analytics (BDA) as an essential instrument for e-commerce companies. This literature survey offers a complete summary of the central function of BDA within the e-commerce environment, taking cues from new scholarly works found in prominent databases such as Scopus and Web of Science. Its range covers fundamental definitions, the changing traits of big data, and its diverse uses in e-commerce areas like customer analytics, supply chain improvement, and detecting fraud. Additionally, this review outlines different methods utilized for BDA, which feature bibliometric analysis, machine learning, and solutions based on cloud computing. A detailed critique compares current models, traces citations between articles, and pinpoints important voids in the research. The document finishes with a synthesis of major business consequences, a description of current obstacles—covering technical, ethical, organizational, and regulatory fields—and suggests a research plan for the future to promote innovation and lasting development in the digital marketplace.
II. LITERATURE SURVEY A. Evolution & Definitions The concept of big data, defined by its "three main features of variety, volume, and velocity", and subsequently broadened with "veracity and value", became a key topic of academic inquiry circa 2010, with its most rapid evolution occurring from 2011 forward. Prior to this, e-commerce itself began its journey with the advent of online shopping in the 1990s, with commercial activities officially integrating into the internet domain by 1991. The impact of BDA on ecommerce became greatly noticeable after 2014, signifying a period of rapid adoption and perceived benefits. Big Data Analytics (BDA) is described as the integration of big data with analytics, creating business analytics. A broader definition states BDA is "the process of analyzing big data that provides a vision to make business decisions". This comprehensive method entails gathering, analyzing, applying, and interpreting data from multiple operational units to derive useful intelligence, generate commercial worth, and secure a competitive edge.
Key Words: Big Data Analytics; E-commerce; Innovation; Predictive Analytics; Machine Learning; Supply Chain Management; Customer Behavior.
I.
INTRODUCTION
An unparalleled data explosion, frequently called "big data," has marked the digital age, produced by pervasive online technologies like digital sensors and cloud computing. In the e-commerce sector, this effect is especially noticeable, as it has experienced substantial expansion and change following its beginnings in the 1990s. E-commerce, defined as commercial transactions conducted through digital channels and internet-based platforms, includes a wide array of operations, spanning from internet-based purchasing and sales to complex supply chains and client support. Research into Big Data Analytics (BDA) for e-commerce finds strong motivation from its vital function in advancing innovative enterprises and company performance, particularly amid major disruptions such as the COVID-19 pandemic. E-commerce companies can endure and prosper with BDA by expanding their activities and executing informed choices using key intelligence from large-scale data. Businesses that utilize BDA show markedly greater productivity and expansion, highlighting its significance as a primary competitive advantage and a core catalyst for innovation and marketplace victory. This paper aims to provide a structured literature review on Big Data in E-commerce. Section II surveys the existing
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Fig. 1. Evolution of BDA adoption among Fortune 1000 companies from 2010–2024.
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