Data profiling
Examining a dataset to describe what is actually in it: types, ranges, distinct values, blanks, and patterns, column by column.
Profiling comes first. It replaces what you assume about a file with what is true of it, and most cleaning decisions follow from the profile.
See also
- CardinalityThe number of distinct values in a column. A country column has low cardinality; an email column has high cardinality.
- Data typeThe kind of value a column holds, such as text, whole number, decimal, date, or true and false. The type decides what operations make sense.
- OutlierA value far from the rest of its column. It may be an error, or it may be the most interesting row in the file.