Significant work has been conducted in the past to understand the thermodynamic variables and parameters that influence the environmental conditions of the rooms vis-a-vis the computer room air conditioning (CRAC) units, racks and servers. A considerable amount of data had been collected from environmental sensors located at various locations within data centers, measuring the supply and return air temperatures in the CRAC units and both inlet and outlet temperatures in the racks. This work describes the analysis done to discover and classify trends and patterns and relationships within temperatures and air flow data in a data center. Initially exploratory data analysis (EDA) techniques were used for reduction of data, visualization of deterministic behavior and identification of normal or abnormal environmental behavior in the control process. Principal Components Analysis (PCA) was used to capture the variables that contain the information about the influence of CRAC units over the racks. 7 Pages