A SYSTEMATIC MAPPING REVIEW OF DATA WAREHOUSE SOLUTIONS IN DATA MANAGEMENT
DOI:
https://doi.org/10.33003/fjs-2026-1001-4424Keywords:
Big Data, Data, Data Warehouse, Data Management, Database Management SystemAbstract
Organizations heavily rely on data for operations, analysis and data-driven business support decisions for productivity, profitability and growth. Numerous data warehouse solutions exist with varying scope, capabilities and comparative strengths which most industry players are not aware of. Therefore, this paper is concerned about systematically mapping the research on Data Warehouses for Data Management by identifying and characterizing the publication landscape, the gaps, research focus and methods. The papers were selected using filtering and inclusion. Study design and time frames were used to get papers from academic databases. The papers were screened using the titles, review of abstracts, which were followed by full-text review for relevant papers. Evaluation of papers were undertaken by answering Research Questions (RQs), summarizing and presenting the results from the primary studies in tables and charts for ease of analysis. The research findings using 30 reviewed papers showed Lakehouse and Hybrid are the most used Data Warehouse architectural styles followed by Cloud Natives. Data Base Management System is still the most prevalent technology for Data Warehouse storage. Scalability and Throughput are the most reported factors in Data Warehouse cost optimization. In conclusion, security, maintainability, reliability and data quality are the most identified attributes affecting Data Warehouse quality.
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Copyright (c) 2026 Mpi Chimekwa, Bilkisu Muhammad-Bello, Ibrahim Anka Salihu, Joshua Abah
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