Respuesta :
An important issue that associated with the loading component of extract, transform, load (ETL) is monitor refreshing volume and frequency.
Data from many sources are extracted, transformed, and loaded through the ETL process into a data warehouse or another centralized data repository. The data integration process known as ETL, or extract, transform, and load, brings together data from several data sources into a single, consistent data store that is then loaded into a data warehouse or other destination system.
ETL, a procedure for integrating and loading data for computation and analysis, was established as databases gained popularity in the 1970s. Eventually, it became the main way to process data for data warehousing projects.
Workstreams in data analytics and machine learning are built on the basis provided by ETL. ETL cleans and arranges data according to a set of business rules in order to address particular business intelligence needs.
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