When non-data people asks "did you validated the data", my understanding is simply "did you double checked the results?".
They don't really get that once a data model is running, you don't get much deviation (if any). They're used to manual calculations where there's a lot of user error, so they want you to make sure you haven't skipped any step and so on.
If your analysis is automated, to "validate" your data basically means to check if all your parameters are correct and if there's isn't any new value on the dataset that is not being considered and messing up other values.
The above is for more general data analysis type of thing. However if you are doing actual data science (creating a statistic model to try and predict the future and whatnot), validating the model could mean a lot of other things (which I don't have the knowledge to get into)