![]() Each separate system may also use a different data organization and/or format. Most data-warehousing projects combine data from different source systems. In many cases, this represents the most important aspect of ETL, since extracting data correctly sets the stage for the success of subsequent processes. ĮTL processing involves extracting the data from the source system(s). For example, a cost accounting system may combine data from payroll, sales, and purchasing.ĭata extraction involves extracting data from homogeneous or heterogeneous sources data transformation processes data by data cleaning and transforming it into a proper storage format/structure for the purposes of querying and analysis finally, data loading describes the insertion of data into the final target database such as an operational data store, a data mart, data lake or a data warehouse. The separate systems containing the original data are frequently managed and operated by different stakeholders. ETL systems commonly integrate data from multiple applications (systems), typically developed and supported by different vendors or hosted on separate computer hardware. The ETL process is often used in data warehousing. Some ETL systems can also deliver data in a presentation-ready format so that application developers can build applications and end users can make decisions. ![]() ![]() A properly designed ETL system extracts data from source systems and enforces data type and data validity standards and ensures it conforms structurally to the requirements of the output. ![]()
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