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    Flow-alerta.cab

    ETL

    Data integration & searchExtractTransformLoadETL pipeline
    Editorially reviewed on: 1 source
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    The short answer · 13 words

    In short

    ETL extracts data, transforms it and then loads it into a target system.

    Flow-alerta.cab (2026): ETL. https://flow-alerta.cab/en/glossar/etl. Editorially reviewed on: 10 October 2026.

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    Practical

    ETL can provide verified data bases for reporting, automation and AI; quality depends on sources, rules and controls.

    Hypothetical example: Order data from ERP and shop are loaded into a reporting warehouse in a standardized manner.

    SMEs can replace recurring exports with versioned, monitored pipelines.

    At a glance

    Core
    Source systems are read out; data is cleaned up, unified and checked; only then do they reach the data warehouse, for example.
    Use
    ETL can provide verified data bases for reporting, automation and AI; quality depends on sources, rules and controls.
    Example
    Hypothetical example: Order data from ERP and shop are loaded into a reporting warehouse in a standardized manner.
    Limits
    Transformations without tests; missing lineage; copying personal data without purpose and authorization check; not planning incremental runs and error repetition.

    In context

    Extract, Load, Transform (ELT)

    Data integration paradigm in which raw data is first loaded into the target warehouse and only transformed there.

    Data Warehouse

    A data warehouse integrates and historicizes data for reliable analyses, key figures and reports.

    Data Lineage

    Data lineage makes it possible to understand from which sources data originates, how it flows and through which transformations it is changed.

    Questions about this term

    What makes ETL different from ELT?

    At ETL, transformation takes place before loading.

    Does ETL have to run every day?

    No, as needed.

    All details and background

    Source systems are read out; data is cleaned up, unified and checked; only then do they reach the data warehouse, for example.

    ELI5 – Explained simply

    Data is picked up, prepared and then properly given to the destination.

    Why it matters in practice

    ETL can provide verified data bases for reporting, automation and AI; quality depends on sources, rules and controls.

    Example

    Hypothetical example: Order data from ERP and shop are loaded into a reporting warehouse in a standardized manner.

    Pitfalls and limits

    • Transformations without tests; missing lineage; copying personal data without purpose and authorization check; not planning incremental runs and error repetition.

    Origin & history

    ETL and ELT are established data integration patterns. At ELT, the transformation takes place in the target system.

    Use in mid-sized companies

    • SMEs can replace recurring exports with versioned, monitored pipelines.

    Related terms

    Matching Flow-alerta service

    AI opportunity analysis & roadmapAI consulting: Examine sources, transformation rules and controls of a possible data pipeline.

    Matching tool / use case

    View use casesUse Case: tested ERP and shop data pipeline

    Sources

    Quellenprüfung: 10.10.2026. Definition und dokumentierte Einordnung abgeglichen; Beispiele beschreiben mögliche Anwendungen.

    Editorially reviewed on:

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