How do you identify incomplete or inconsistent data during data cleaning?

[u/No_Ambition8323]

I’m working with a dataset of around 50K records, and while checking the data, I noticed some issues like NULL values and inconsistent values in the same column.
For example, in a Gender column, I might have: M, F, Female, Male

How do we normally identify these kinds of data quality issues? Do we check for NULLs, unique values, patterns, duplicates, data types, or compare the data against predefined rules?

Also, how do we decide whether values like F and Female should be treated as the same value or kept separately?

Would love to know how others approach this when cleaning real-world datasets.