AiVibeExtract, Transform, Load (ETL)
Extract, transform, load (ETL) is a data integration process that pulls data from source systems, cleans and reshapes it, and loads it into a target such as a data warehouse; ELT loads raw data first and transforms it inside the target.
Extract, transform, load (ETL) is a data integration process that extracts data from source systems, transforms it by cleaning, standardising, joining and aggregating, and loads the result into a target such as a data warehouse. In the related ELT pattern, raw data is loaded first and transformed inside the target platform using its compute, an approach that became common with scalable cloud warehouses and lakehouses.
ETL and ELT pipelines feed reporting, analytics and machine learning with consistent data from ERP, MES, CRM, historians, files and APIs. Tools range from managed services such as AWS Glue, Azure Data Factory and Google Cloud Dataflow to open-source projects such as Apache Airflow for orchestration and dbt for SQL-based transformation inside the warehouse. Change data capture is often used to extract only the rows that have changed.
Reliable pipelines need idempotent steps that can be rerun safely, data quality checks, handling of schema changes, monitoring and clear ownership. Batch pipelines introduce latency between source and report, so time-sensitive use cases may move to streaming ingestion. Lineage records which sources and transformations produced each dataset, supporting debugging, audits and data protection obligations.
Key points
- ETL transforms data before loading; ELT loads first and transforms in the target
- Feeds warehouses, lakes and analytics from ERP, MES, historians, files and APIs
- Tools include AWS Glue, Azure Data Factory, Apache Airflow and dbt
- Idempotent steps, quality checks and lineage make pipelines reliable
Where AiVibe comes in
AiVibe Software Services delivers cloud solutions on AWS, Microsoft Azure, Google Cloud or on-premise, together with cloud security, legacy modernisation, data analytics and AI and machine learning services.
Related terms
- Data WarehouseCloud & AI Infrastructure
- Data LakeCloud & AI Infrastructure
- Data LakehouseCloud & AI Infrastructure
- Event StreamingCloud & AI Infrastructure
- Manufacturing Execution System (MES)Industry 4.0 & Manufacturing Operations