methodology

ETL Process

ETL (Extract, Transform, Load) is a data integration methodology used to combine data from multiple sources into a centralized repository, typically a data warehouse or data lake. It involves extracting data from various systems, transforming it to meet business requirements (e.g., cleaning, aggregating, standardizing), and loading it into a target destination for analysis and reporting.

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

Developers should learn ETL processes when building data pipelines for business intelligence, analytics, or data migration projects, as it ensures data quality and consistency across systems. It's essential in scenarios like consolidating customer data from CRM and ERP systems, preparing data for machine learning models, or complying with data governance regulations.

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