# ETL (Extract, Transform, Load)

> ETL (extract, transform, load) is a data integration process that pulls data from source systems, cleans and reshapes it into a consistent format, and loads it into a destination such as a data warehouse or reporting database. A variant, ELT, loads raw data first and transforms it inside the destination. ETL pipelines usually run on a schedule or continuously.

## Why it matters for your business

Most reporting and many AI projects depend on data from several systems landing in one place in a consistent shape. Without a pipeline, someone exports spreadsheets and merges them by hand each week, with errors and delays. ETL also prepares data for AI: a natural-language reporting tool or a forecasting model is only as good as the tables it reads. Key decisions include which system is the source of truth for each field, how often to refresh, and how to handle records that fail validation.

## Example

A multi-location restaurant group pulls daily sales from its POS, labor hours from payroll and invoices from accounting into a cloud warehouse each night. The pipeline standardizes location names and dates, and a dashboard shows labor and food cost by location. Managers can also ask questions in plain English through a natural-language SQL assistant built on those tables.

Related terms: https://www.lumeor.studio/glossary/api-application-programming-interface/, https://www.lumeor.studio/glossary/ipaas-integration-platform-as-a-service/, https://www.lumeor.studio/glossary/workflow-automation/, https://www.lumeor.studio/glossary/observability/

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Source: https://www.lumeor.studio/glossary/etl-extract-transform-load/