Extract, Transform, Load (ETL) Task

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An Extract, Transform, Load (ETL) Task is a data processing task that involves data extraction, data transformation and data loading into a database.



  • (Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/Extract,_transform,_load Retrieved:2017-11-8.
    • In computing, extract, transform, load (ETL) refers to a process in database usage and especially in data warehousing. The ETL process became a popular concept in the 1970s. [1] Data extraction is where data is extracted from homogeneous or heterogeneous data sources; data transformation where the data is transformed for storing in the proper format or structure for the purposes of querying and analysis; data loading where the data is loaded into the final target database, more specifically, an operational data store, data mart, or data warehouse.

      Since the data extraction takes time, it is common to execute the three phases in parallel. While the data is being extracted, another transformation process executes while processing the data already received and prepares it for loading while the data loading begins without waiting for the completion of the previous phases.

      ETL systems commonly integrate data from multiple applications (systems), typically developed and supported by different vendors or hosted on separate computer hardware. The separate systems containing the original data are frequently managed and operated by different employees. For example, a cost accounting system may combine data from payroll, sales, and purchasing.