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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

Full-Text Search
A technique for searching natural language text in databases using word stemming, ranking, and relevance scoring.
Replication
The process of copying and maintaining database data across multiple servers for redundancy, failover, and read scaling.
Trigger
A database object that automatically executes a specified function when certain events (INSERT, UPDATE, DELETE) occur on a table.
Query Optimization
The process of improving database query performance through indexing, query rewriting, and schema design techniques.
Prepared Statement
A pre-compiled SQL template that uses parameters instead of literal values, preventing SQL injection and improving performance.
B-Tree Index
The default index type in most databases that organizes data in a balanced tree structure for efficient searching, sorting, and range queries.
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