International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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A Review and Comparative Study on the Impact of Data Warehouse Data Models on Business Intelligence and Decision Support Systems

Author(s) Ramya K, Rashmi Ajith
Country India
Abstract In the modern data-driven organizational environment, organizations increasingly rely on Business Intelligence (BI) systems to convert large volumes of data into meaningful insights for decision-making. A critical factor influencing the effectiveness of BI systems is the underlying data model used to organize and store data. This study examines the impact of different data models—specifically the Star Schema and Snowflake Schema—on business intelligence performance.

The research adopts a descriptive and comparative approach using secondary data structured in a data warehouse environment. Both Star and Snowflake schemas are implemented using SQL, and their performance is evaluated based on query execution efficiency, reporting accuracy, analytical flexibility, and decision- support effectiveness. The findings reveal that the Star Schema offers superior query performance and simplicity, making it highly suitable for dashboard-driven and operational BI applications. Conversely, the Snowflake Schema enhances data integrity and supports complex hierarchical analysis, making it more appropriate for strategic and enterprise-level analytics. The study concludes that data model selection plays a decisive role in BI effectiveness and that a hybrid modelling approach can help organizations balance performance with analytical depth
Keywords Data Warehouse, Star Schema, Snowflake Schema, Business Intelligence, Decision Support Systems
Field Computer Applications
Published In Volume 8, Issue 1, January-February 2026
Published On 2026-01-20
DOI https://doi.org/10.36948/ijfmr.2026.v08i01.66799
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E-ISSN 2582-2160
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