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Decision Support Systems - Module II (6 ECTS): LABORATORY OF DATA SCIENCE (2026/2027)

This is the second module of Decision Support Systems (801AA, 12 ECTS), previously called Laboratory of Data Science (664AA, 6 ECTS).

Instructors:

Always email both instructors and include [LDS] at the beginning of the subject line.

The following is the timetable for the whole Decision Support Systems course. The two modules span differently over the semester. The first module will take most of the lessons from September to October. The second module will take most of the lessons from November to December.

Day of Week Hour Room
Tuesday 11:00 - 13:00 Fib H-Lab
Wednesday 11:00 - 13:00 Fib C1
Thursday 14:00 - 16:00 Fib C
Friday 09:00 - 11:00 Fib C

A Teams channel (TBD) is used to post news, Q&A, and other stuff related to the course. The lectures will be held in person only and will NOT be live-streamed, but recordings of the lectures from this or previous years will be made available to non-attending students. The recording publication could receive some delays (one week of delays).

Learning Material

Slides & Recordings of the classes

  • The slides used in the course will be inserted in the calendar after each class.
  • Recordings of each lecture will be made available for non-attending students.

Past Exams

To prepare yourself for the practical test, you can use these past exam exercises on: programming (using Python instead of Java), SSIS, and MDX.

Software

Note: preconfigured virtual machines will be available to download in the Teams channel for both AMD64 (Intel/AMD) and ARM (Apple Silicon) architectures. The virtual machines come with all the required software installed and tested, except for Microsoft Excel: you can download it for free from office.com using your University credentials.

F.A.Q.

Class calendar - (2026-2027)

N. Day Topic Lecture Material Video Lectures Refs Teacher
1. 18.09 Introduction to the Course. BI Architectures. Introduction to the course Bi Architecture Video1 Video2 - BI technology: An Overview of Business Intelligence Technology - File access: File System Interface Monreale
2. 22.09 File data access. Python Recap. File Data Access Python Recap supplementary code Video - File Formats: Introduction to data technologies(Chps. 5, 6), Weka ARFF Format, XRFF Format - Python reference: Free python book with exercises Monreale
3. 23.09 Python Excercises + File Access in Python File Access in Python Video Landi
4. 24.09 Python File Access + Exercises Data ex files Video Monreale, Landi
5. 25.09 Python File Access + Exercises ex-customers.pdf data-customers.zip Exercise solutions Video Ex. Project Presentation
6. 06.10 RDBMS access protocols + Python DB Access + Project Presentation
7. 13.10 Exercises correction + Stratified sampling Exercise
8. 20.10 Python DB Access: exercises
9. 27.10 SQL Server + SSIS + ToCSV + FromCSV
10. 28.10 SSIS: Pipeline + Stratified Sampling assignmt
11. 29.10 Correction of exercise in python on customers
12. 03.11 SSIS:Update, Surrogate Keys
13. 11.11 Correction of Stratified Sampling + SCD workflow for new customers
14. 17.11 SCD workflow for update customers + SSIS practice
15. 18.11 SSIS practice + Solutions of Dissimilarity and MPD
16. 19.11 CDC Process
17. 24.11 Introduction to SSAS + DW 1) SSAS (olap): documentation; 2) S. Harinath et al. Professional Microsoft SQL Server Analysis Services 2012 with MDX and DAX, Wrox publisher, 2012. Chps. 4-6
18. 25.11 Olap Cube Instructions for the SSAS project: to avoid conflicts in deployment/process follow this steps once the solution is opened: (1) rename the project as <your account>_foodmart (2) from project properties select 'Deployment', then rename the database as <your account>_foodmart; (3) click on the button “show all files” just above “Solution explorer” right click on “view code” on the .database file that is visualized, and then change the ID from current name into <your account>_foodmart, and finally save the file. (4) change the credentials of connection to database on SQL Server.
19. 27.11 PROJECT CHECK -MANDATORY
20. 01.12 Metrics + Excel power pivot integration
21. 03.12 MDX Queries
22. 04.12 MDX Queries
23. 09.12 MDX Queries
24. 10.12 PowerBI + MDX practice

Exams

The exam of Decision Support Systems (801AA, 12 ECTS) consists of a written part and an oral part on the topics of the first module (50% of the final grade), and a lab project or written test with discussion on the topics of the second module (50% of the final grade). See Module I: Decision Support Databases for the theory part. The project of Module II can be discussed only after passing Module I and not later than one year since then.

The lab project must be submitted by the specified deadline. If the project is not submitted within the deadline, a practical test and a discussion on the topics of the second module will be required for the exam instead.

PROJECT A project consists of a set of assignments corresponding to a BI process: data integration, construction of an OLAP cube, querying of the OLAP cube, and reporting.

The project has to be performed by a team of 3 students.

Exam sessions

Registration to the written exam is mandatory (pay attention at the deadline for registering!): register here

Please indicate in the notes “Only Lab” for doing only the discussion of the lab project; “Only DSD” for doing only the written+oral part of the DSD module; or “DSD+Lab” for doing both.

Important: The date of the lab project discussion will be communicated to you by the instructors. The dates reported in the registration website refear only the written part of the DSD module.

How to book a slot for the practical test? For students who need to do the practical test during the exam session because they did not deliver the project, they must report their studentID in the dates listed in this shared document: Pratical Test booking. Available dates are: 5th June 20206, 19th June 2026, 7th July 2026. If you have important issues with these dates, please write an email to the teachers asap.

Past Editions

mds/lbi/start.txt · Ultima modifica: da Anna Monreale

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