Changing a set of scores that were in the form of number correct into a set of scores that now represent percent, is an example of data transformation.
The process of changing the format, structure, or values of data is known as data transformation. Data can be modified at two points in the data pipeline for initiatives including data analytics. Data transformation serves as the middle phase in an ETL (extract, transform, load) process, which is commonly used by businesses with on-premises data warehouses.
The benefits of data transformation are:
•Data that has been transformed might be simpler to use for both people and machines.
•The compatibility of applications, systems, and data formats is made possible by data transformation. It could be necessary to modify data differently if it is utilized for different reasons.
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