Data Quality Quacks: Completeness

Completeness refers to the degree to which all data in a data set is available
it also measures if the data is sufficient to deliver meaningful inferences and decisions.
Most of us know how to identify a duck because we know what a duck looks like and what features it has.
But what if you were teaching a 5 year old about ducks? What features do you need to include to make sure that the data complete enough to correctly identify the duck?
Ducks are relatively small, have a short neck, webbed feet, flat bills, and can be multicolored.
- If you omit the short neck data, you might confuse a goose for a duck
- If you omit the coloring, you might confuse a swan for a duck
TL;DR
Make sure that you include all the data points in order to make the best decision.
What is your favorite waterfowl?
Do you have a data completeness story?