ETL

ETL stands for Extract, Transform, Load, a data integration process used to collect data from one or more sources, transform it into a consistent format, and load it into a destination system.

ETL is commonly used in data warehouses, analytics platforms, reporting systems, and large-scale data processing workflows.

Also known as: Extract-Transform-Load, ETL pipeline, ETL process.

How Does ETL Work?

An ETL workflow consists of three main stages:

1. Extract data from source systems.
2. Transform the data into the required format.
3. Load the processed data into the destination.

The goal is to make data from different sources consistent, reliable, and ready for analysis.

Extract

The Extract stage collects data from one or more sources.

Common sources include:

• Databases
• APIs
• CSV files
• Applications
• Log files
• Cloud platforms
• Websites

The extracted data may be structured, semi-structured, or unstructured.

For example, a company may collect customer records from a CRM system, transaction data from a database, and product information from an API.

Transform

The Transform stage cleans, standardizes, and prepares the extracted data.

Common transformation tasks include:

• Removing duplicates
• Converting data types
• Standardizing date formats
• Normalizing currencies
• Renaming fields
• Validating records
• Combining datasets
• Calculating new values

For example:

Original value:
Price: USD 49.99
Date: 10/15/2026

may be transformed into:

Price: 49.99
Currency: USD
Date: 2026-10-15

The transformation stage ensures that downstream systems receive consistent data.