International Journal For Multidisciplinary Research

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

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Streamlining data integration: Architectures for Real-Time Insights and On-Demand Transformation

Author(s) Mr. Shamnad Mohamed Shaffi, Mx. Jezeena Nikarthil Sidhick
Country United States
Abstract This article explores the emerging concept of Zero-ETL, a modern approach to data integration that seeks to address the limitations of traditional Extract, Transform, Load (ETL) processes. As organizations demand faster insights and real-time data access, the complexities and inefficiencies of traditional ETL become increasingly apparent. Zero-ETL minimizes data movement, integrates data at query time, and leverages technologies such as real-time streaming and data virtualization. The article compares Zero-ETL to traditional ETL, highlighting differences in process, data latency, complexity, flexibility, and infrastructure costs. It discusses the benefits of Zero-ETL, including real-time data availability, simplified operations, cost savings, improved data governance, and scalability. The article also addresses the trade-offs and challenges associated with Zero-ETL, such as infrastructure demands, legacy system integration, and security risks. Best practices for optimal data performance and real-world applications of Zero-ETL in machine learning, customer experience analytics, fraud detection, and supply chain optimization are presented. Finally, the article outlines key considerations for building a Zero-ETL architecture and reviews the technology landscape, including AWS, Snowflake, and Databricks. This comprehensive overview aims to provide organizations with the insights needed to leverage Zero-ETL in their data integration strategies
Keywords Real-Time Data Integration, Data Virtualization, Query-Time Transformation, Streaming Analytics, Federated Querying, Cloud Data Architecture, Data Pipeline Optimization, Schema-on-Read, ETL Modernization
Field Computer > Data / Information
Published In Volume 7, Issue 3, May-June 2025
Published On 2025-05-04
DOI https://doi.org/10.36948/ijfmr.2025.v07i03.43843
Short DOI https://doi.org/g9hsks
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