Perceived Data Quality

I have an application that relies on an extensive dataset that people (trader/market analysts) make decisions on. I have a huge dataset and I want to know what is the perceived quality of the data, to an unbiased person (i.e they don't say "I don't like this data" , "It was not good before" ...)

My data contains many variables (let's say 50) that can be delayed, missing or inaccurate. For the sake of this exercise, I will say they all have the same importance.

Quality (for me) is freshness (~not missing), understandability and precision

A. Perfect Case: All values are perfect (quality = 100) then the dataset has a 100% quality.

B. One variable not perfect: All value are perfect except one (quality = 50)

C. All variables almost perfect: All values are almost perfect (quality = 99)

What is the quality you would put to the overall dataset in cases B and C. And as a user, when would you want an alert to be raised, on what format ?