We aim to analyze students results in exams. The designer advocated a mixed approach. On the one hand, he relies on the study of the analytical requirements requested by the university and by a committee that examines the results, and on the other hand by examining the data source model described by the relational database of exams. Below is a partial description of this database: STUDENT (STD-NO, FName, LName, Birth-Date, Gender, Housing, Tel, ID-FAC# FACULTY (ID-FAC, Name, Short-Name, Address, MODULE (ID-CORS, Name, ID-SPEC#, Semester, SPECIALTY (ID-SPEC, Name, Nb-Years, RESULTS (STD-NO #, ID-CORS#, Acad-Year, Semester, Mid-Term1-Mark, Mid-Term2-Mark, Final-Exam-Mark, Average-Mark, Final-Grade, Queries below constitute a non-exhaustive list of the main analytical requirements: 1) Numbers of students in each Course who succeeded in the Mid-Term1, split by academic year and by Faculty. 2) Average mark by Course and by Faculty. 3) Success rate per Course and gender of students. 4) Number of students who succeed in each course per academic year and Faculty. 5) Average score per course and Faculty. 6) Success rate per course and gender of students. 7) Percentage of failure per course. 8) Total number of students per faculty and specialty. 9) Final (end of year) success rate of students per gender. Questions: 1) Identify Subject of Analysis. 2) Considering the above relational data source model and the given requirements, elaborate a sheet giving for each identified fact its measures, dimensions and their attributes as well as the matching with the data source and the extraction expressions. 3) Draw a multidimensional star schema