Kwame, Mensah and Dr. Sofia, Almeida and Dr. Jonathan, Reed (2025) OPTIMIZING FINANCIAL WORKLOAD PIPELINES: COMPARATIVE STUDY OF DISTRIBUTED QUERY PROCESSING IN TERADATA, HIVE SQL, AND PYSPARK FOR ENTERPRISE-SCALE RISK MODELING APPLICATIONS. Manuscripts on the Artificial Intelligence and Digital Research, 2 (8). pp. 56-72. ISSN 3064-8807

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Abstract

The increasing complexity of enterprise-scale financial risk modeling has created an urgent demand for high-performance, scalable, and resilient data processing pipelines. Banks and financial services institutions (BFSI) must integrate vast volumes of structured and unstructured data, ranging from transactional records to regulatory disclosures, under stringent time and compliance constraints. Traditional approaches often struggle with latency, scalability, and governance challenges, making distributed query processing a critical enabler of modern risk analytics.

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 08:35
Last Modified:	18 Sep 2025 08:35
URI:	http://eprints.umsida.ac.id/id/eprint/16359

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