These terms often appear in discussions about data management, and it's easy to assume they are either the same thing or completely unrelated. Surprisingly, while they serve different purposes, they are complementary rather than contrasting.
Data cleansing, also known as data cleaning or data scrubbing, involves identifying and correcting errors and inconsistencies in data to improve its quality. On the other hand, data enrichment is the process of enhancing existing data by adding additional information from external sources.
In summary, data enrichment and data cleansing are not competing processes. They serve different purposes but work together to improve data quality and usability.
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