A Comprehensive Framework for Big Data Analytics: Core Elements, Implementation, and Strategic Insights

Rampant growth in web data due to increased growth at zetta byte scales driven by various types of online data sources including online commerce websites, social networks, web sensors, business websites, and user communities has given a boost to extracting valuable information with the help of Big Data Analytics (BDA). The key strength of BDA is that it can process large datasets and reveal underlying trends. Optimizing BDA processes, though, is a challenge since it involves combining different data assets to produce actionable insights. This paper explores the BDA process and what it can do through three case studies of leading BDA tool users. The research uncovers four core elements of the BDA framework: system coordination, data sourcing, big data application services, and end-user interaction. Besides, key supporting factors such as data security, privacy, and management act as fundamental functions that complement these elements throughout the information and technology value chain.

Authors

Institutions

Publication Details

Journal
International Journal of Scientific Research in Science and Technology
Published
2025-03-15
DOI
https://doi.org/10.32628/ijsrst25122226
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Comprehensive Framework for Big Data Analytics: Core Elements, Implementation, and Strategic Insights

Darshanaben Dipakkumar Pandya, Dipikaben Umakant Thakar, Khushbu
International Journal of Scientific Research in Science and Technology
Big Data and Business Intelligence
article

A Comprehensive Framework for Big Data Analytics: Core Elements, Implementation, and Strategic Insights

Darshanaben Dipakkumar Pandya, Dipikaben Umakant Thakar, Khushbu
article en

Abstract

Rampant growth in web data due to increased growth at zetta byte scales driven by various types of online data sources including online commerce websites, social networks, web sensors, business websites, and user communities has given a boost to extracting valuable information with the help of Big Data Analytics (BDA). The key strength of BDA is that it can process large datasets and reveal underlying trends. Optimizing BDA processes, though, is a challenge since it involves combining different data assets to produce actionable insights. This paper explores the BDA process and what it can do through three case studies of leading BDA tool users. The research uncovers four core elements of the BDA framework: system coordination, data sourcing, big data application services, and end-user interaction. Besides, key supporting factors such as data security, privacy, and management act as fundamental functions that complement these elements throughout the information and technology value chain.

International Journal of Scientific Research in Science and TechnologyVol. 12(2)
University of Madras (IN), Manubhai Patel Dental College and Hospital (IN)
Openalex Percentile: Top 93%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.