Cloud vs. On-Premise Data Warehousing: A Strategic Analysis for Financial Institutions

The transformation of data warehousing in financial services marks a pivotal shift in how institutions manage and utilize data assets. Financial organizations navigate complex decisions between cloud-based, on-premise, and hybrid solutions, each offering distinct advantages and challenges. The evolution encompasses enhanced security protocols, improved regulatory compliance mechanisms, and advanced analytical capabilities. Modern implementations demonstrate substantial improvements in operational efficiency, cost optimization, and system performance. The integration of artificial intelligence and machine learning technologies has revolutionized predictive analytics and automation capabilities. Financial institutions leveraging these advanced solutions experience significant enhancements in data processing speeds, security measures, and cross-platform compatibility. The progression toward hybrid architectures represents a strategic balance between security requirements and scalability needs, enabling organizations to maintain control over sensitive data while accessing cloud-based capabilities for specific workloads.

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Publication Details

Journal
Journal of Computer Science and Technology Studies
Published
2025-05-07
DOI
https://doi.org/10.32996/jcsts.2025.7.3.57
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.28
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article

Cloud vs. On-Premise Data Warehousing: A Strategic Analysis for Financial Institutions

Preeta Pillai
1 citations
Journal of Computer Science and Technology Studies
Big Data and Business Intelligence
2.28
article

Cloud vs. On-Premise Data Warehousing: A Strategic Analysis for Financial Institutions

Preeta Pillai
article en
1 citations

Abstract

The transformation of data warehousing in financial services marks a pivotal shift in how institutions manage and utilize data assets. Financial organizations navigate complex decisions between cloud-based, on-premise, and hybrid solutions, each offering distinct advantages and challenges. The evolution encompasses enhanced security protocols, improved regulatory compliance mechanisms, and advanced analytical capabilities. Modern implementations demonstrate substantial improvements in operational efficiency, cost optimization, and system performance. The integration of artificial intelligence and machine learning technologies has revolutionized predictive analytics and automation capabilities. Financial institutions leveraging these advanced solutions experience significant enhancements in data processing speeds, security measures, and cross-platform compatibility. The progression toward hybrid architectures represents a strategic balance between security requirements and scalability needs, enabling organizations to maintain control over sensitive data while accessing cloud-based capabilities for specific workloads.

Journal of Computer Science and Technology StudiesVol. 7(3)
Biju Patnaik University of Technology (IN)
Openalex Percentile: Top 12%
Big Data and Business Intelligence
2.28
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Cloud vs. On-Premise Data Warehousing: A Strategic Analysis for Financial Institutions — Preeta Pillai · Journal of Computer Science and Technology Studies (2025) | TGRS Research Map | TGRS