Regardless of how much precision is available, there is still the problem that some numbers cannot be represented exactly. This is the principle reason for difficulty in storing fractional numbers in floating-point representation. This lack of precision is aggravated by arithmetic operations. The sums become imprecise as the values continue. The number is close, but never exactly 0.
Imprecision can also cause problems with comparisons.
As discussed in Floating-Point Representation , the SAS System allows for numeric values to be stored on disk with less than full precision. For example, the IBM mainframe representation uses 8 bytes for full precision, but you can store as few as 2 bytes on disk. In 2 bytes, it would be truncated to 41 10. A decrease in the number of digits means either fewer digits to the right of the decimal place or fewer digits to the left of the decimal place before trailing zeroes must be used. All values are expanded to full size to perform computations in DATA and PROC steps.