User:Scholarlycoffee/Extract, Transform, Load (ETL) on cloud/Bibliography

Background
The process of connecting to different types of data sources and extracting the data from them, transforming that data according to business rules, and finally loading them into a warehouse can be summed up into ETL (Extract, Transform, and load). The different sources would be OLTP databases, flat files, cloud and spreadsheets, etc. The purpose of integrating these many sources of data is to help decision-makers in getting an overview of business and make data-driven decisions for the future. The ETL tools available in the market are a one-stop shop for performing all the functionalities required for creating a warehouse and also accomplishing other data projects such as data conversion, data migration, data cleaning, data governance, and data quality.

According to, the different models of ETL processes could be mapping expressions and guidelines, conceptual constructs, and unified modeling language (UML) environment. Common examples of ETL tools are Informatica PowerCenter, IBM DataStage, Talend, ab initio, etc.

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