Defectivity data from a 4MB DRAM manufacturing process was analyzed using a visual data mining methodology based on Parallel Coordinates. Parallel Coordinates provides an interactive framework for analyzing multi-variate data graphically using 2-D graphs that can be colored using visual queries. These graphs provide a unique mapping of multivariate data to 2-D without any loss of information. Using this methodology, some defects were found that were actually "beneficial" and in small quantities improved the yield and speed performance (access time) of the wafer. While using conventional methods, the yield on the wafers couldn't be improved beyond a plateau and hence had led the engineers to think of redisgning the chip, the process window discovered using the Parallel Coordinate methodology provided some insights that helped in improving the yield of the process significantly. This technique is extremely useful in yield analysis and improvement, process control and design of experiments.