The evolution of ETL architecture: From traditional data warehousing to real-time data integration

Nishanth Reddy Mandala *

Independent Researcher, USA.
 
Review Article
World Journal of Advanced Research and Reviews, 2019, 01(03), 073–084
Article DOI10.30574/wjarr.2019.1.3.0033
 
Publication history: 
Received on 09 March 2019; revised on 23 April 2019; accepted on 26 April 2019
 
Abstract: 
This paper explores the evolution of Extract, Transform, Load (ETL) architectures, tracing the shift from traditional, batch-oriented ETL processes in data warehousing to realtime data integration frameworks. ETL has been a fundamental component in enabling data warehousing and business intelligence for several decades. However, the demand for faster insights and real-time decision-making has driven ETL towards real-time data integration solutions. This paper discusses traditional ETL methods, examines the changes leading to real-time ETL, and explores architectural patterns and challenges associated with each paradigm.
 
Keywords: 
ETL; Data Warehousing; Real-Time Integration; Data Transformation; Business Intelligence
 
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