Summary form only given. A huge wealth of various data exist in the practice of software development. Further rich data are produced by modern software and services in operation, many of which tend to be data-driven and/or data-producing in nature. Hidden in the data is information about the quality of software and services and the dynamics of software development. Software analytics is to develop and apply data exploration and analysis technologies, such as pattern recognition, machine learning, and information visualization, on software data to obtain insightful and actionable information for modern software and services. This tutorial presents latest research and practice on principles, techniques, and applications of software analytics in practice, highlighting success stories in industry, research achievements that are transferred to industrial practice, and future research and practice directions in software analytics. The attendees can acquire the skills and knowledge needed to perform industrial research or conduct industrial practice in the field of software analytics and to integrate analytics in their own industrial research, practice, and training.