ETL

Data from several data sources are combined into a single, consistent data store using the data integration technique known as ETL, or extract, transform, and load. This consistent data storage is then put into a data warehouse or other destination system. As a method for integrating and loading data for computation and analysis, ETL was first presented. Eventually, it took over as the main technique for processing data for data warehousing projects. On the foundation that ETL provides, workstreams in data analytics and machine learning are constructed. ETL can handle more advanced analytics that could improve back-end operations or end-user experiences. It cleans and arranges data using a set of business rules to satisfy specific business intelligence requirements, including monthly reporting. ETL is frequently used by a company to extract information from old systems, Cleanse the data to increase its uniformity and quality, and Insert data into the desired database.

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