Here we will see what is data cleansing? And the list of data cleansing steps to avoid data issues.

Firstly, bad data causes a lot of problems such as

• Lower Marketing Returns
• Reputational Damage
• Lost Sales Opportunities
• Lower User Confidence
• Inaccurate Reports

Bad data means it could be

• Missing data
• Inaccurate Data
• Duplicates
• Out-Of-Date Data

Secondly, Data Decays Everyday people move houses and name changes, etc. If you are not cleansing your data on monthly basis the chances are your data is decade up to 25% in a year.

Cleansing international data even is more difficult especially language, data country formats, and other aspects.

How do you create outstanding data?

Here are the data cleansing steps and methodologies.

1. Place everything in the right place
2. Cleanse and Fix
3. Uncovering duplicates
4. Commercially choose the master record
5. Commercially combining duplicates
6. Add data intelligence

It is too costly to have bad data in your systems. This six data cleansing steps approach can help you to clean, accurate and current data.

I hope it helps.