It’s understandable why someone may confuse data enrichment with data cleansing since they’re related to data hygiene.
Data cleansing involves detecting and removing inaccurate or corrupt data. On the other hand, data enrichment only refers to refining, improving, or enhancing third-party raw data to integrate with an existing data set.
A good data cleansing process involves cross-checking and validating already existing data, whereas data enrichment, by definition, focuses only on the data added. However, the line is getting thinner as many advanced tools offer a mix of both data enrichment and data cleansing services.