A comprehensive framework for cloud data warehouse adoption: Best practices, pitfalls and key considerations

Cloud data warehouse adoption represents a transformative shift in enterprise data management, enabling organizations to scale and optimize their analytics capabilities in flexible, cost-effective environments. This article examines the comprehensive framework required for successful implementation spanning architectural considerations, organizational readiness, industry-specific patterns, and future directions. The exploration covers reference architectures, migration strategies, integration approaches, security governance, change management practices, and cultural transformation requirements essential for maximizing value. Through examination of implementation patterns across financial services, healthcare, retail, and manufacturing sectors, the article identifies both common success factors and distinctive industry considerations. The framework presented addresses not only technical deployment but also the equally critical human dimensions that determine whether capabilities translate into business outcomes. Long-term management considerations and emerging trends including lakehouse architectures, data observability, and AI integration complete the holistic view of effective cloud data warehouse adoption.

Authors

Publication Details

Journal
World Journal of Advanced Engineering Technology and Sciences
Published
2025-06-06
DOI
https://doi.org/10.30574/wjaets.2025.15.3.0886
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
0.00
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article

A comprehensive framework for cloud data warehouse adoption: Best practices, pitfalls and key considerations

Purushotham Jinka
World Journal of Advanced Engineering Technology and Sciences
Cloud Computing and Resource Management
article

A comprehensive framework for cloud data warehouse adoption: Best practices, pitfalls and key considerations

Purushotham Jinka
article en

Abstract

Cloud data warehouse adoption represents a transformative shift in enterprise data management, enabling organizations to scale and optimize their analytics capabilities in flexible, cost-effective environments. This article examines the comprehensive framework required for successful implementation spanning architectural considerations, organizational readiness, industry-specific patterns, and future directions. The exploration covers reference architectures, migration strategies, integration approaches, security governance, change management practices, and cultural transformation requirements essential for maximizing value. Through examination of implementation patterns across financial services, healthcare, retail, and manufacturing sectors, the article identifies both common success factors and distinctive industry considerations. The framework presented addresses not only technical deployment but also the equally critical human dimensions that determine whether capabilities translate into business outcomes. Long-term management considerations and emerging trends including lakehouse architectures, data observability, and AI integration complete the holistic view of effective cloud data warehouse adoption.

World Journal of Advanced Engineering Technology and SciencesVol. 15(3)
Openalex Percentile: Top 82%
Cloud Computing and Resource Management
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