In our articles related to AI and Big Data in healthcare, we always talk about ETL as the core of the core process. We do not write a lot about ETL itself, though. In this post, we’ll give a short overview of this procedure and its applications in businesses.
ETL is the abbreviation for Extract, Transform, Load that are three database functions:
Extract is the process of reading data that is assumed to be important. The data can be either raw collected from multiple and different types of sources or taken from a source database.
Transform is the process of converting the extracted data from its previous format into the format required by another database. The transformation occurs by using rules or lookup tables or by combining the data with other data.
Load is the process of writing the data into the target database, data warehouse or another system
ETL in its essence is a type of data integration used to blend data from multiple sources.
ETL vs. ELT
The ETL paradigm is inherent to Data Warehousing, and Big Data has significantly changed the order of the processes. In Big Data, data is “lifted and shifted” wholesale to a repository, such as a Data Lake, and is held there in the …
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