Defaults mistaken for data

A value that looks real was filled in automatically by a form or a system, and nobody actually chose it.

What it looks like

Before

After

country	birth_date	check
Afghanistan	1900-01-01	both match the form defaults, likely never entered
Afghanistan	1988-07-19	country matches the default, needs a decision
Canada	1970-01-01	birth date matches a common system default, needs a decision
Canada	1991-03-22	no default values

Nothing is changed. Some people really do live in the first country on the list, so a default value is a reason to check, not proof of an error.

A dropdown opens on its first option, and people submit without changing it.
A database column has a default, so a missing value is stored as zero, false, or a fixed date.
A conversion turned empty dates into the earliest date the system supports.

One category is far larger than it should be, which skews every breakdown by that field.
Missing data is undercounted, because the cells are not empty.
The default is a valid value, so no validation rule catches it.

Look for one value that is far more common than the rest, especially the first option in the form's list.
Look for dates that pile up on the first day of a year, or on the starting date a system counts from.
Compare with related fields. A country that disagrees with the postal code or phone prefix was probably not chosen.

Find out what the defaults are from the form or the system that produced the data. That evidence is outside the file.
Where a default cannot be a real value for the column, such as an order date long before the organization took its first order, replace it with a true empty cell.
Where the default could be real, do not clear it. Flag it, and check it against other fields or with a person.
Change the form so the field starts empty, and new rows stop arriving with the same problem.

Disguised missing valuesA cell is not empty, but what it holds means there is no value: N/A, a dash, 999, or the word none.
True blanksA cell is really empty, and the file does not say whether the value is unknown, not applicable, or was never asked for.
Outliers from entry errorsA value sits far outside the rest because of a slipped key, an extra zero, or a misplaced decimal point.
Case example: UtilitiesEquipment records that could not be tied to what was spent on them