Building Effective Cloud Migration Assessment Frameworks: A Structured Approach for Enterprise Transformation

This article presents a comprehensive framework for developing and implementing cloud migration assessment methodologies that enable organizations to systematically evaluate their readiness for cloud adoption. The proposed framework integrates technical evaluation criteria, cost analysis methods, risk assessment approaches, and organizational readiness evaluation into a cohesive assessment model. By examining both the technical landscape and the human factors that influence migration success, this article provides decision-makers with structured tools to identify potential challenges, quantify migration costs, select appropriate migration strategies, and develop effective mitigation plans. Through practical templates, real-world case studies, and methodological guidance, the article offers actionable insights for organizations at various stages of cloud maturity. The framework addresses common pitfalls in migration planning while emphasizing the importance of aligning technical transformation with business objectives and organizational capabilities. This integrated approach enables more predictable, cost-effective, and successful cloud migration initiatives that deliver expected business value.

Authors

Institutions

Publication Details

Journal
Global Journal of Engineering and Technology Advances
Published
2025-04-19
DOI
https://doi.org/10.30574/gjeta.2025.23.1.0090
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

Building Effective Cloud Migration Assessment Frameworks: A Structured Approach for Enterprise Transformation

Pavankumar Yanamadala
Global Journal of Engineering and Technology Advances
Big Data and Business Intelligence
article

Building Effective Cloud Migration Assessment Frameworks: A Structured Approach for Enterprise Transformation

Pavankumar Yanamadala
article en

Abstract

This article presents a comprehensive framework for developing and implementing cloud migration assessment methodologies that enable organizations to systematically evaluate their readiness for cloud adoption. The proposed framework integrates technical evaluation criteria, cost analysis methods, risk assessment approaches, and organizational readiness evaluation into a cohesive assessment model. By examining both the technical landscape and the human factors that influence migration success, this article provides decision-makers with structured tools to identify potential challenges, quantify migration costs, select appropriate migration strategies, and develop effective mitigation plans. Through practical templates, real-world case studies, and methodological guidance, the article offers actionable insights for organizations at various stages of cloud maturity. The framework addresses common pitfalls in migration planning while emphasizing the importance of aligning technical transformation with business objectives and organizational capabilities. This integrated approach enables more predictable, cost-effective, and successful cloud migration initiatives that deliver expected business value.

Global Journal of Engineering and Technology AdvancesVol. 23(1)
Sheffield Hallam University (GB)
Openalex Percentile: Top 88%
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.

Building Effective Cloud Migration Assessment Frameworks: A Structured Approach for Enterprise Transformation — Pavankumar Yanamadala · Global Journal of Engineering and Technology Advances (2025) | TGRS Research Map | TGRS