Dynamically analyzing diagnostic operations data via machine learning techniques

Methods, systems, and computer program products for dynamically analyzing diagnostic operations data via machine learning techniques are provided herein. A computer-implemented method includes defining aspects of machine learning techniques to be performed in connection with diagnostic operation data analysis, including: defining dynamic analysis granularity selection functionality based on time constraints and the level of progress of the analysis; defining dynamic data classification identifier type selection functionality based on the time constraints and the level of progress of the analysis; and defining dynamic ordering of data classification identifiers during runtime based on data classification preferences, information pertaining to system workload, and information pertaining to requested analysis compliance parameters. The method also includes dynamically performing the analysis by applying the machine learning techniques to the diagnostic operation data, and outputting at least a portion of results of the analysis.