Profiling job activities on different batch systems in the data center helps understand the patterns of usage by different users. With these patterns the system administrators in the data center are able to reorganize or rearrange their resources in a way that the overall resource utilization is improved. In this paper, we extract wall and CPU time from job accounting information on different batch systems of which Global Science experiment Data hub Center (GSDC) at Korea Institute of Science and Technology Information (KISTI) provides to its various user communities and we profile job activities of each batch system for months. We evaluate batch system usage and prioritize jobs upon the profiles.