Mariana, Costa and Dr. Arjun R., Mehta and Dr. William T., Harris (2025) Scalable Semantic Data Models for Enterprise Analytics: Designing Unified Architectures in Tableau and Power BI to Support Multi-Functional BFSI Risk, Fraud, and Compliance Dashboards. Insight: Advances in Research in Radiophysics and Electronics, 2 (5). pp. 6-20. ISSN 3064-7274

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Abstract

The increasing complexity of enterprise data environments in BFSI has highlighted the need for scalable, semantic data models that enable unified, multi-functional analytics across risk, fraud, and compliance domains. Traditional dashboard implementations in tools like Tableau and Power BI often suffer from fragmented data structures, inconsistent metrics, and scalability limitations, which hinder accurate decision-making and regulatory reporting.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Postgraduate > Master's of Islamic Education
Depositing User:	Journal Editor
Date Deposited:	18 Sep 2025 08:25
Last Modified:	18 Sep 2025 08:25
URI:	http://eprints.umsida.ac.id/id/eprint/16358

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