Creating successful learners is a challenging task for educational institutions. As a rule, the measurement of student learning performance is carried out using tests and exams. However, tests and exams data are often subjected to inadequate analysis, which leads to incorrect conclusions about the progress of student learning; misleading recommendations on how to improve the learning process. Using innovative statistical and machine-learning methods and proprietary algorithms, A-Scala analyzes tests and exams data and provides accurate and reliable information about each student learning performance. A-Scala creates Student Success Profiles for each course and quantifies its components. A-Scala identifies gaps in student knowledge and suggests ways to address them, helping educators lead students to success in their field of education. A-Scala is solely based on the SAS System. This paper provides an overview of A-Scala capabilities and presents a real-life case study.