Values analysis is often useful as the first type of analysis to perform on relatively unknown data. It helps determine the nature and overall quality of the data, by reporting whether data is categorical or continuously numeric, how many null values, and so on. You can apply values analysis to any type of character or numeric data, even date fields.
Given a table and column name, the Values analysis provides the number of:
- Rows
- Rows with non-null values
- Rows with null values
- Rows with value 0
- Rows with a positive value
- Rows with a negative value
- Rows containing blanks in the given column.
For a column of non-numeric type, the zero, positive, and negative counts are always zero. For example, “ 000” is not counted as 0.
The Values analysis is parameterized by specifying the table and columns to analyze, the optional Group By column, and the Output or Expert Options.