ETL vs ELT: Evolving Approaches to Data Integration

Author(s)	Ramakanth Reddy Vanga
Country	United States
Abstract	This article explores the evolution of data integration approaches, focusing on the transition from Extract, Transform, Load (ETL) to Extract, Load, Transform (ELT) methodologies. It examines the characteristics, advantages, and challenges of both approaches in the context of modern data management requirements. The article discusses the factors driving the shift towards ELT, including cloud adoption, big data growth, real-time analytics demands, and the rise of data lake architectures. Additionally, it presents best practices for implementing ELT, covering areas such as data cataloging, version control, data quality checks, performance optimization, and security compliance. Through analysis of industry trends and real-world use cases, the article provides insights into why organizations are increasingly adopting ELT frameworks and the considerations involved in this transition.
Keywords	Keywords: Data Integration, ETL, ELT, Cloud Computing, Big Data
Field	Computer
Published In	Volume 6, Issue 5, September-October 2024
Published On	2024-10-28
Cite This	ETL vs ELT: Evolving Approaches to Data Integration - Ramakanth Reddy Vanga - IJFMR Volume 6, Issue 5, September-October 2024. DOI 10.36948/ijfmr.2024.v06i05.29481
DOI	https://doi.org/10.36948/ijfmr.2024.v06i05.29481
Short DOI	https://doi.org/g8pnjt

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International Journal For Multidisciplinary Research