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ETL (Extract, Transform, Load)

The ETL (Extract, Transform, Load) is a process of extracting data from different sources, transforming it to clean and harmonise it, then loading it into a target system (data warehouse, data lake…).
It forms the backbone of data projects in companies, allowing tounify heterogeneous sources to derive coherent analyses from them.

Related Services

Data Engineering

Related Terms

Data Engineering Scraping XML Feeds Migration

ETL in practice

Typical Use Cases

  • Populating a data warehouse from multiple systems (CRM, ERP, web, IoT).
  • Synchronising two business applications.
  • Transfer historical data during a migration.
  • Preparing data for an AI model.

ETL or ELT?

  • ETL - transformation before loading, ideal when volume is controlled.
  • ELT - raw loading then transformation in the data warehouse, more flexible with modern tools (dbt + Snowflake / BigQuery).

Caveats

  • Idempotence - a job that runs twice must produce the same result.
  • Error management - automatic retries, alerts.
  • Latency vs freshness - daily batch, streaming, or near-real-time depending on the need.

How Galadrim can support you

See our offering Data Engineering.

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