Manuscript Number : IJSRSET221655

ETL Best Practices : Transforming Raw Data into Business Insights

Authors(1) :-N V Rama Sai Chalapathi Gupta Lakkimsetty

Extract, Transform, Load (ETL) processes play a critical role in modern data management, enabling organizations to extract raw data, transform it into meaningful formats, and load it into analytical systems for business insights. With the advent of big data, cloud computing, and AI-driven analytics, ETL has evolved significantly. This paper explores best practices in ETL processes, discussing key strategies for optimizing data extraction, transformation, and loading. The research provides insights into modern ETL architectures, including ELT, data mesh, and serverless ETL solutions, while highlighting challenges related to security, compliance, and performance scalability.

Authors and Affiliations

N V Rama Sai Chalapathi Gupta Lakkimsetty
Independent Researcher, USA

ETL, Data Transformation, Data Warehousing, Big Data, AI-Driven ETL, Cloud Computing, Data Governance

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Publication Details

Published in : Volume 9 | Issue 4 | July-August 2022
Date of Publication : 2022-07-14
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 533-546
Manuscript Number : IJSRSET221655
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

N V Rama Sai Chalapathi Gupta Lakkimsetty , " ETL Best Practices : Transforming Raw Data into Business Insights, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 9, Issue 4, pp.533-546, July-August-2022. Journal URL : https://res.ijsrset.com/IJSRSET221655

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