IJBTT

Scaling Data Engineering with Advanced Data Management Architecture: A Comparative Analysis of Traditional ETL Tools Against the Latest Unified Platform
	© 2024 by IJCTT Journal
	Volume-72 Issue-10
	Year of Publication : 2024
	Authors : Paulami Bandyopadhyay
	DOI :  10.14445/22312803/IJCTT-V72I10P105

How to Cite?

Paulami Bandyopadhyay, "Scaling Data Engineering with Advanced Data Management Architecture: A Comparative Analysis of Traditional ETL Tools Against the Latest Unified Platform," International Journal of Computer Trends and Technology, vol. 72, no. 10, pp. 22-30, 2024. Crossref, https://doi.org/10.14445/22312803/IJCTT-V72I10P105

Abstract
This technical article critically examines the strengths and advantages of the modern data analytics platform in comparison to legacy ETL (Extract, Transform, Load) tools through an in-depth exploration of key features, performance, scalability, ease of use, and integration capabilities. This article will highlight how the advancement in technology has resulted in offering superior capabilities in terms of real-time processing, scalability, agility, advanced analytics, unified platforms, governance, security, deployment flexibility, cost efficiency, and ecosystem integration compared to traditional ETL processes. These advantages make them crucial for organizations aiming to maximize the value of their data assets and foster innovation in their business operations. There are diverse options available for implementing a new data pipeline or upgrading the existing orchestration mechanism. This article tends to do a thorough analysis by carefully evaluating these benefits, weaknesses, and considerations. Researchers and industry specialists can make informed decisions about selecting the appropriate ETL components or considering alternative data integration and processing approaches (such as ELT, streaming data platforms, or modern data analytics tools) that better suit their specific requirements and use cases.

Keywords
BI Tools, Data management, Data visualization, ETL, Unified Platform.

Reference

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