![]() ![]() This shift leverages the capabilities of modern data warehouses, enabling faster data ingestion and reducing the complexities associated with traditional transformation-heavy ETL processes. ELT advocates for loading raw data directly into storage systems, often cloud-based, before transforming it as necessary. The paradigm shift from ETL to ELT-Extract, Load, Transform-signals a fundamental change in data processing strategies. Data now flows in from disparate sources-enterprise databases, IoT devices, and web APIs, among others-posing a challenge in harmonizing and integrating this diverse data landscape within the confines of traditional ETL workflows ![]()
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