The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • GIDP 2026
  • ICONS_BA 2025

Computer Vision Conference (CVC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • RSS Feed

DOI: 10.14569/IJACSA.2025.0160742
PDF

Empirical Validation and Enhancement of ADiBA: A Framework for Big Data Analytics Implementation

Author 1: Norhayati Daut
Author 2: Naomie Salim
Author 3: Sharin Hazlin Huspi
Author 4: Anazida Zainal
Author 5: Chan Weng Howe
Author 6: Muhammad Aliif Ahmad
Author 7: Siti Zaiton Mohd Hashim
Author 8: Masitah Ghazali
Author 9: Mohd Adham Isa
Author 10: Rashidah Kadir
Author 11: Nuremira Ibrahim
Author 12: Norazlina Khamis

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 16 Issue 7, 2025.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: The implementation of Big Data Analytics (BDA) in organisations requires a structured approach to ensure alignment with strategic goals and infrastructure readiness. This study presents an enhanced version of the previously published ADiBA (Accelerating Digital Transformation Through Big Data Adoption) framework that aimed at guiding organizations through critical components necessary for successful BDA implementation. The initial framework was developed based on systematic literature review. To validate and refine the framework, a mixed-methods survey was conducted among domain experts using a five-point Likert scale and open-ended questions to assess the relevance of each framework component. Quantitative responses were analysed using the Content Validity Index (CVI), with a threshold of 0.78 adopted as the minimum acceptable I-CVI score for each item. Complementing the quantitative analysis, qualitative feedback from the open-ended survey responses, Focus Group Discussions (FGDs), and in-depth interviews were examined through thematic analysis, revealing key themes related to framework’s clarity and operational aspects. Insights from both analyses informed the refinement of several components. The resulting framework is a validated and empirically-informed guide designed to support effective BDA implementation in organizational contexts.

Keywords: Adoption process; big data; big data analytics; framework; framework validation; expert survey; content validity index; thematic analysis; organizational implementation; digital transformation

Norhayati Daut, Naomie Salim, Sharin Hazlin Huspi, Anazida Zainal, Chan Weng Howe, Muhammad Aliif Ahmad, Siti Zaiton Mohd Hashim, Masitah Ghazali, Mohd Adham Isa, Rashidah Kadir, Nuremira Ibrahim and Norazlina Khamis. “Empirical Validation and Enhancement of ADiBA: A Framework for Big Data Analytics Implementation”. International Journal of Advanced Computer Science and Applications (IJACSA) 16.7 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0160742

@article{Daut2025,
title = {Empirical Validation and Enhancement of ADiBA: A Framework for Big Data Analytics Implementation},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160742},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160742},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {7},
author = {Norhayati Daut and Naomie Salim and Sharin Hazlin Huspi and Anazida Zainal and Chan Weng Howe and Muhammad Aliif Ahmad and Siti Zaiton Mohd Hashim and Masitah Ghazali and Mohd Adham Isa and Rashidah Kadir and Nuremira Ibrahim and Norazlina Khamis}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

Computer Vision Conference (CVC) 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

Artificial Intelligence Conference 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Future Technologies Conference (FTC) 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computer Vision Conference
  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

The Science and Information (SAI) Organization Limited is a company registered in England and Wales under Company Number 8933205.