After you have identified and assessed the risk, look at all the aspects which the risk will affect. This will help you to plan the remedial actions and tackle the risk.

For example you came across unclean data during the extraction process, as a consultant, you should flag this by looking at different areas which will be impacted. A small dataset may not cause significant changes, but if it's a large dataset, it can impact several dashboards.

One of the important but most neglected aspects of risk is making the client aware of it. One of the aspects is the impact it will have on the existing project. The other aspect is what action can the client take to make newer data clean.

So, what could be the impacts of unclean data. Some areas which we can think of are: 

• Data modelling issues
• Incorrect data on dashboards
• Reduced end user experience
• Time and costs in data cleansing
• Change in application logic for workarounds

As a consultant, start planning on actions which can help you control the risk. Some action points can be (not all may be applicable):

• Clean the data at source (this may be the toughest one)
• At Extract, Transform and Load (ETL) layer, write scripts to clean the data which goes in to Qlik data file (qvd)
• Create intermediate master, mapping the incorrect values with correct values
• Proactively engage with the users, make them aware of the issue, and make them aware of the action items