A new attribute reduction algorithm was developed to improve the process of computing discernibility matrices in decision tables. By focusing on the number of non-null objects, the algorithm reduces time and memory usage. The importance of attributes is defined and a quick formula is provided to calculate it. The new algorithm minimizes the number of attributes needed for reduction, as demonstrated in example analysis.