You can choose either to use the raw numeric values, or to normalize the values per item (that is, per column in the data table). The normalized values are standard scores (z-scores) per item. Normalizing makes sense if the values in the different data columns were measured using different scales or have different ranges.
Note that multiple values per cell cannot be used in numeric processing. Cells with missing data should not be left empty, but be marked with NA.