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In managing databases, extract, transform, load (ETL) refers to three separate functions combined into a single programming tool. First, the extract function reads data from a specified source database and extracts a desired subset of data. Next, the transform function works with the acquired data - using rules or lookup tables, or creating combinations with other data - to convert it to the desired state. Finally, the load function is used to write the resulting data (either all of the subset or just the changes) to a target database, which may or may not previously exist.
ETL can be used to acquire a temporary subset of data for reports or other purposes, or a more permanent data set may be acquired for other purposes such as: the population of a data mart or data warehouse; conversion from one database type to another; and the migration of data from one database or platform to another.
ETL can be contrasted with ELT (Extract, Load, Transform) which transfers raw data from a source server to a data warehouse on a target server and then prepares the information for downstream uses.
Continue Reading About extract, transform, load (ETL)
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- The Good, the Bad, and the Ugly of Extract Transform Load (ETL) –Incorta
- Optimising the data warehouse –ComputerWeekly.com