ETL (Extract, Transform, Load)

ETL (Extract, Transform, Load) commonly refers to a data integration process used to move data from one or more source systems into a target system such as a database, data warehouse, reporting layer, analytics platform, or another business application.

The three steps are:

• Extract: collect data from source systems such as MES, ERP, LIMS, SCADA, historians, QMS, or spreadsheets.
• Transform: clean, map, standardize, enrich, validate, or restructure the data so it fits the target model and intended use.
• Load: write the processed data into the destination system.

In manufacturing and regulated operations, ETL is often used to consolidate production, quality, maintenance, inventory, or traceability data for reporting, analytics, master data alignment, or cross-system interoperability. For example, ETL may pull work order data from ERP, production events from MES, and test results from a quality system into a central reporting environment.

ETL is a data movement and preparation pattern, not the business system itself. It does not by itself define operational workflows, approvals, or record retention rules, although it may support those processes by making data available in a consistent format.

Operational meaning

In practice, ETL appears as scheduled jobs, pipelines, scripts, middleware, or integration platform workflows. Transformations may include unit conversions, code mapping, deduplication, timestamp normalization, batch or lot matching, and data quality checks. Loads may be full, incremental, or event-driven depending on system design.

Where auditability matters, teams often pay attention to source-to-target mappings, change control, data lineage, error handling, and whether the destination is used for reporting only or for operational decision-making.

Common confusion

ETL is often confused with ELT. In ETL, data is transformed before or during loading into the target. In ELT, raw data is loaded first and transformed inside the destination platform.

It is also commonly confused with general system integration or API integration. ETL is one integration approach focused on moving and reshaping data. Not all integrations are ETL, and not all ETL flows are real-time APIs.

Another common confusion is with a data migration. A migration is typically a one-time or bounded move from one system to another. ETL more often refers to ongoing or repeatable data pipelines.