Software quality assurance and planning of an astronomy project is a complex task, specially if it is a distributed collaborative project such as ALMA, where the development centers are spread across the globe. When you execute a software project there is much valuable information about this process itself that you might be able to collect. One of the ways you can receive this input is via an issue tracking system that will gather the problem reports relative to software bugs captured during the testing of the software, during the integration of the different components or even worst, problems occurred during production time. Usually, there is little time spent on analyzing them but with some multidimensional processing you can extract valuable information from them and it might help you on the long term planning and resources allocation. We present an analysis of the information collected at ALMA from a collection of key unbiased indicators. We describe here the extraction, transformation and load process and how the data was processed. The main goal is to assess a software process and get insights from this information.