Handle Data 

In order to have the best Color Supply Chain experience on the long run, we have considered to create a brief summary of the optimal Data Hygiene process. We suggest you, to consider reading through this document and avoid any inappropriate data stored.

Data Hygiene is the process of ensuring the correct availability of the data. This includes the process of removing incorrectly uploaded and duplicated data, this also includes the deletion of the unused data. Any inappropriate setup can cause a problem, especially if the amount unwanted data grows too big. These can definitely cause data hygiene problem in your production system.

“The collective processes conducted to ensure the cleanliness of data. Data is considered clean if it is relatively error-free. Dirty data can be caused by several factors, including duplicate records, incomplete or outdated data, and the improper parsing of record fields from disparate systems. Errors can be introduced at any stage as data is entered, stored and managed.” - TechTarget


We have collected some examples on our system, that can cause complication.

Measure with CWH Data Hygiene Metrics

It is possible to measure data hygiene in ColorWarehouse. The Data Hygiene Metrics chart compile the number of unfulfilled fields on some system fields:

  • Fabric ID
  • Mill Name
  • Mill Port

Updates are on the way: 

Currently this function only monitoring the three system fields above. Soon the retailer will be able to add any of their specific custom fields and expand the inspected fields. This update will make possible to have more accurate data hygiene measures in ColorWarehouse.

Import data through ASAP Excel Importer:

  • Always make sure the mapping and the excel spreadsheet’s content are appropriate!
  • Always check the Process Results Log after uploading a file!
  • Always check the file name you want to process.

If you have any special reason of uploading "dirty data" (e.g. PLM requirement), please feel free to contact us. We will do our best to work out a possible solution to optimize data cleanliness.