Building a ETL pipeline

Building a ETL pipeline

Building a ETL pipeline using Python, Pandas, and MySQL. An ETL (Data Extraction, Transformation, Loading) pipeline is a set of processes used to Extract, Transform, and Load data from a source to a target.

An ETL (Data Extraction, Transformation, Loading) pipeline is a set of processes used to Extract, Transform, and Load data from a source to a target. The source of the data can be from one or many sources, such as from an API call, CSV files, information within a database, and many more. We take these sources of information then transform it in a way where it can be used immediately by another client, user or developer within some target storage. In practice, an ETL pipeline is run infrequently. Generally there are large amounts of information that is unfiltered and difficult to process and clean, often taking large amounts of time and resources to transform.

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