methodology

ETL

ETL (Extract, Transform, Load) is a data integration process that involves extracting data from various sources, transforming it into a structured format, and loading it into a target system such as a data warehouse or database. It is fundamental for data warehousing, business intelligence, and analytics, enabling organizations to consolidate and clean data from disparate systems for reporting and decision-making.

Also known as: Extract Transform Load, Data Integration, Data Pipeline, ETL Process, Data Warehousing
🧊Why learn ETL?

Developers should learn ETL when working on data pipelines, data warehousing projects, or any application requiring data migration, integration, or quality improvement. It is essential for scenarios like aggregating sales data from multiple platforms, cleaning customer records for CRM systems, or preparing datasets for machine learning models, as it ensures data consistency and reliability.

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