Filling the Data Quality Expectation Gap...

 

As a project moves towards Go-live stakeholders are often surprised by on-going data quality issues. "You said the data was clean!" If you are experiencing this expectation gap, the main problem is most likely you! YOU have to set the expectation that data quality is going to be an on-going, iterative process.

 

Data Quality in Design

- Data is cleansed based on 'known' business and system rules.

(no one knows all the rules)

- Then we go to testing and learn more about the data.

 

Data Quality in Testing

- Testing Defects - data is cleansed again

- Data is cleansed based on testing scenario defects (no one will test all the scenarios)

 

Data Quality at Go-live

- Hypercare Defects: data is cleansed again

- guess we missed a few rules and scenarios

 

Data Quality in Production

- the business changes the rules

- the system needs to be optimized

- organizational changes

- user errors

- interface errors

- materials, customers, and vendors phase in and out.

 

Data quality is a process that will never go away and will always demand the attention of your stakeholders. Talk about this early and often if you are leading a data team!