Data Cleansing refers to the organization and editing of raw data as it is stored in a data warehouse. A standardized cleansing process prevents business logic confusion and errors. For example, a client could have a POS system and a speed of service solution that title their day-parts differently. One system refers to day-parts as "breakfast, lunch, and dinner" while the other system uses "breakfast, lunch, supper, and late night". If you combine the data from both systems into your data warehouse and use it for reporting, there is going to be business logic issues. We help clients by creating cleansing rules that all systems will follow to prevent future reporting problems.
Mirus organizes and edits raw data from any system in any location for our clients. This process is important because it reduces wasted time in "Excel-Hell", prevents human errors, and allows clients to use data they can trust instead of relying on intuition to make business decisions.
“Net sales between net sales of different point of sale systems is the same across the board with Mirus. That basically takes apples and oranges and says here this is fruit juice, this is how it’s supposed to be.”
- Point of Sale Manager, Dewey's Pizza