The category of a data value — such as integer, text, date, or boolean — that determines how it is stored and processed.
Every field in a dataset has a data type. Common types include integer (whole numbers), decimal or float (numbers with fractions), text or string (characters), date and datetime, and boolean (true/false). The data type controls what operations are valid — you can add two integers but not two text strings.
Example: A dataset of election results has a votes column (integer), a candidate_name column (text), an election_date column (date), and an incumbent column (boolean). Knowing the types tells you immediately what calculations and comparisons are valid for each column.
Data type mismatches are a common source of errors. A postal code stored as an integer loses its leading zero (e.g., 01234 becomes 1234). Always check data types when opening a new dataset.