Systems Analyst: What is ETL vs ELT and when to use each?

ETL (Extract, Transform, Load): Transform before loading into warehouse.

ELT (Extract, Load, Transform): Load raw data first, transform in warehouse.

ETL:

• Transform in middleware (SSIS, Informatica, dbt).
• Clean data before loading.
• Better for small data volumes.
• Requires separate compute for transformation.

ELT:

• Load raw data into warehouse (BigQuery, Snowflake, Redshift).
• Transform using SQL in the warehouse.
• Leverages warehouse compute power.
• Better for large data volumes.

When to use ETL:

• Sensitive data needing masking before storage.
• Limited warehouse compute.
• Complex transformations not supported in SQL.

When to use ELT:

• Cloud data warehouses with ample compute.
• Need to retain raw data for auditing.
• Data lake architectures.

Tools:

• ETL: Informatica, Talend, SSIS.
• ELT: dbt, Snowflake, BigQuery.