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eISSN: 2581-9615 || CODEN (USA): WJARAI || Impact Factor: 8.2 || ISSN Approved Journal

Innovations in data lake architectures for financial enterprises

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  • Innovations in data lake architectures for financial enterprises

Abhilasha Hala Swamy *

Goldman Sachs, USA.

Review Article

World Journal of Advanced Research and Reviews, 2025, 26(01), 1975-1982

Article DOI: 10.30574/wjarr.2025.26.1.1252

DOI url: https://doi.org/10.30574/wjarr.2025.26.1.1252

Received on 07 March 2025; revised on 13 April 2025; accepted on 15 April 2025

This article explores recent innovations in data lake architectures within financial enterprises, highlighting their crucial role in modern financial data management. The content examines how financial organizations leverage data lakes to process structured and unstructured data for advanced analytics and decision-making. The discussion covers evolving architectural components from ingestion to consumption layers, the rise of data lake houses as hybrid solutions, real-time data processing capabilities, AI/ML integration for predictive analytics, and comprehensive governance frameworks addressing security and compliance concerns. By providing insights into technical implementations and practical applications, the article offers a roadmap for financial institutions seeking to optimize their data infrastructure to meet current demands for data-driven decision making while maintaining regulatory compliance.

Data Lake House Architecture; Financial Data Governance; Real-Time Stream Processing; Predictive Financial Analytics; Regulatory Compliance Automation Retry Claude Can Make Mistakes. Please Double-Check Responses

https://journalwjarr.com/sites/default/files/fulltext_pdf/WJARR-2025-1252.pdf

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Abhilasha Hala Swamy. Innovations in data lake architectures for financial enterprises. World Journal of Advanced Research and Reviews, 2025, 26(01), 1975-1982. Article DOI: https://doi.org/10.30574/wjarr.2025.26.1.1252.

Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0

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