ETL vs. ELT: Optimizing Data Integration for Retail and Insurance Analytics
Keywords:
ETL, ELT, retail analyticsAbstract
Using inventive solutions in the always evolving data integration environment, retail and insurance industries see vast data sets. Integration of good ETL/ELT data benefits retail and insurance analytics. The research most fit and improve their applicability. Though their effects on data management, performance, scalability, and efficiency differ, ETL and ELT form the foundation of the data processing flow.
Conventional ETL builds a data warehouse for analysis from source system data. This makes logical given data is altered and cleaned before storage. Pre-processing guarantees consistency and quality of data even in cases of transformation requiring time. This paper addresses the context of ETL in data warehouses and advanced data transformation.
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