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  1. Extract, transform, load - Wikipedia

    Extract, transform, load (ETL) is a three-phase computing process where data is extracted from an input source, transformed (including cleaning), and loaded into an output data container. …

  2. ETL Process in Data Warehouse - GeeksforGeeks

    3 days ago · In short, the ETL process involves extracting raw data from various sources, transforming it into a clean format and loading it into a target system for analysis.

  3. Extract, transform, load (ETL) - Azure Architecture Center

    Extract, transform, load (ETL) is a data integration process that consolidates data from diverse sources into a unified data store. During the transformation phase, data is modified according …

  4. What is ETL (extract, transform, load)? - IBM

    What is ETL? ETL—meaning extract, transform, load—is a data integration process that combines, cleans and organizes data from multiple sources into a single, consistent data set …

  5. What is ETL? - Extract Transform Load Explained - AWS

    Extract, transform, and load (ETL) is the process of combining data from multiple sources into a large, central repository called a data warehouse. ETL uses a set of business rules to clean …

  6. What is ETL? - Google Cloud

    ETL stands for extract, transform, and load and is a traditionally accepted way for organizations to combine data from multiple systems into a single database, data store, data warehouse, or data...

  7. What Is The ETL Process & How It Helps You Work With Data …

    3 days ago · Learn how the ETL process works, where it fits in your data warehouse, and how it helps with reporting and analysis.

  8. ETL Process & Tools | SAS

    ETL is a type of data integration that refers to the three steps (extract, transform, load) used to blend data from multiple sources. It's often used to build a data warehouse.

  9. What is ETL (extract transform load)? - Informatica

    ETL is a three-step data integration process used to synthesize raw data from a data source to a data warehouse, data lake, or relational database. Data migrations and cloud data integrations …

  10. ELT vs ETL vs Reverse ETL: Don’t Panic! It’s Just Moving Data

    ETL, ELT, and Reverse ETL explained simply with real-world examples. Learn when to use each and how modern data pipelines really work.