ETL
Extract, Transform, Load
A process for collecting data from various sources, transforming it, and loading it into a final destination. Extract, Transform, Load (ETL) is a crucial data integration process used in data warehousing and business intelligence. It involves three main stages:
- Extract: Data is collected from various sources such as databases, files, APIs, and other repositories. This phase handles challenges like data inconsistencies and different formats.
- Transform: Raw data is cleaned, converted, and standardized to ensure accuracy and consistency. This may involve:
- Filtering out bad data
- Removing duplicates
- Converting data types
- Applying calculations
- Aggregating data
- Applying business rules
- Load: The transformed data is transferred into a target system, typically a data warehouse or data lake. This can involve initial loading of all data followed by incremental updates.
ETL is essential for consolidating data from disparate sources, enabling organizations to have a comprehensive view of their information for analysis and decision-making. The process is often automated to maintain data consistency, eliminate manual errors, and improve efficiency.
