From the course: Hands-On Introduction: Data Engineering
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Extract, transform, load (ETL)
From the course: Hands-On Introduction: Data Engineering
Extract, transform, load (ETL)
- The extract, transform, load pattern is a common approach to building pipelines in the field of data engineering. The ETL process involves extracting data from a source system, transforming it into a format that's suitable for analysis, and loading it into a target system such as a data warehouse or database. Let's look at this visually. In the ETL process, data is extracted into a staging area. That data is then transformed into a format suited for future analysis. Finally, that data is loaded into a persistent storage medium which may be a database, data warehouse, or something else. While not a new concept, ETL is pivotal to the modern data engineer. Historically, ETL has been used in a variety of industries such as finance, healthcare, and retail. One of the earliest examples of ETL can be traced back to the 1960s when banks started to use mainframe computers to process financial transactions. At the time, banks were…
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