Data cleansing is about deduplication, fixing spelling mistakes, standardization, formatting, capitalization, etc. and completeness of the data.

Data quality is - How good is the data? Is the CRM system data better that the ERP system? And the decision maybe is to use “Ship to” data from the ERP system but the CRM system data is better for the “Send to (Invoice)” data.

This can be data that is from one system or from multiple systems.

The better the Data Cleansing and higher the quality - the higher the confidence in the reports and data.  This means that the management team is not spending time discussing what data is right.

If the data is correct, it may mean that you understand the customer the customer better and not in the vacisious position where the customer has better information about the relationship than you do.

For example:
The spelling, once corrected will mean that these two records belong together but also means that the customer is in a higher revenue segment and consequently is in a higher segment. Taken individually the customer falls into a lower segment and often wondered why they are not treated the way they deserve to be treated for the amount of money they have spent.

Pooling for the For example: EZ1 example

Your decisions are only as good as the data those decisions are based on.