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Databases Intermediate

What is ETL (Extract, Transform, Load)?

A data pipeline process that extracts data from sources, transforms it into a suitable format, and loads it into a destination system.

ETL processes move data between systems. Extract pulls data from databases, APIs, files, or streams. Transform cleans, validates, enriches, and restructures the data. Load writes the processed data to a data warehouse or target system.

Modern variations include ELT (load raw data first, transform in the warehouse) and real-time streaming. Tools include Apache Airflow, dbt (transform layer), Apache Spark, and cloud services like AWS Glue. ETL is fundamental to data warehousing and analytics.

Related Terms

Normalization
The process of organizing database tables to reduce data redundancy and improve data integrity.
View
A virtual table defined by a SQL query that provides a simplified or restricted view of data from one or more tables.
Upsert
A database operation that inserts a new row if it does not exist, or updates the existing row if it does.
Database Proxy
A middleware server that sits between applications and databases, providing connection pooling, load balancing, and query routing.
Database Sharding
A horizontal scaling strategy that distributes data across multiple database servers based on a partition key.
Database Connection Pooling
A technique that maintains a cache of database connections for reuse, reducing the overhead of creating new connections.
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