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====== Decision Support Systems - Module II (6 ECTS): LABORATORY OF DATA SCIENCE (2024/2025) ======
This is the second module of [[mds:dss:start|Decision Support Systems]] (801AA, 12 ECTS), previously called Laboratory of Data Science (664AA, 6 ECTS).


**Instructors**:
  * **Anna Monreale**
    * KDD Laboratory, Università di Pisa
    * [[http://pages.di.unipi.it/amonreale/]]
    * [[anna.monreale@unipi.it]] 
    * Office hours: Tuesday: 11:00-13:00 online using Teams or at the Department of Computer Science, room 374/E (Please ask for an appointment by email).
    * Telephone +39-050-2213119

 **Cristiano Landi**
    * KDD Laboratory, Univesità di Pisa
    * [[cristiano.landi@phd.unipi.it]]
    * Office hours: Wednesday: 14:00-16:00 online using Teams or at the Department of Computer Science, room 343 (Please ask for an appointment by email).

**If you are not asking for office hours, 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  |  9:00 - 11:00  |  Fib C  |
|  Wednesday  |  16:00 - 18:00  |  Fib H-Lab  |
|  Thursday  |  11:00 - 13:00  |  Fib A1  |
|  Friday  |  11:00 - 13:00  |  Fib C1  |


A [[https://teams.microsoft.com/l/team/19%3AqCllWc8f7UVglFSVL_MhR4ZjaLlWkUjUvJ3ROQdLSOA1%40thread.tacv2/conversations?groupId=14d45f09-9ae8-4f9f-afd1-114348877094&tenantId=c7456b31-a220-47f5-be52-473828670aa1|Teams channel]] is used to post news, Q&A, and other stuff related to the course. The lectures will be only in presence and will **NOT** be live-streamed, but recordings of the lecture from this or the previous years will be made available for non-attending students. 

====== 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 =====

  * {{ :mds:lbi:2016midterm1text.pdf |2016/17 text}}, {{ :mds:lbi:2015fallmidterm1text.pdf | 2015/16 text}} and {{ :mds:lbi:2015wintermidterm1.zip | 2015/16 solution}}, {{:mds:lbi:2015midterm1text.pdf | 2014/15 text}} and {{ :mds:lbi:2015midterm1.zip |2014/2015 solution}}, {{ :mds:lbi:2014midterm1text.pdf | 2013/14 text}},{{ :mds:lbi:2013midterm1.pdf | 2012/13 text }} and {{ :mds:lbi:2013midterm1.zip |2012/13 solution}}.

===== Software=====

  * Anaconda (Please avoid Python 3.12)
  * SQL Server 2019 Developer Edition or next:[[https://docs.microsoft.com/en-us/sql/ssms/download-sql-server-management-studio-ssms?view=sql-server-ver16|SQL Server 2019 Management Studio]]. 
  * Visual Studio Community 2022. Install/include SSDT workload in installation manager of visual studio: instructions here Italian: [[https://learn.microsoft.com/it-it/sql/ssdt/download-sql-server-data-tools-ssdt?view=sql-server-ver15#ssdt-for-visual-studio-2022|Data Tools Visual Studio 2022 IT]] English: [[https://learn.microsoft.com/en-us/sql/ssdt/download-sql-server-data-tools-ssdt?view=sql-server-ver15#ssdt-for-visual-studio-2022|Data Tools Visual Studio 2022 EN]]. 
  * Microsoft Excel
  * [[https://powerbi.microsoft.com/it-it/desktop/| Power BI Desktop]]

**Note**: preconfigured virtual machines can be found in the [[https://teams.microsoft.com/l/team/19%3AqCllWc8f7UVglFSVL_MhR4ZjaLlWkUjUvJ3ROQdLSOA1%40thread.tacv2/conversations?groupId=14d45f09-9ae8-4f9f-afd1-114348877094&tenantId=c7456b31-a220-47f5-be52-473828670aa1|Teams channel]] for both AMD64 (Intel/AMD) and ARM (Apple Silicon) architectures.

===== F.A.Q. =====
  * [[http://www.sid.unipi.it/polo2/2015/03/26/connessione-alle-reti-wifi/ | Connection to wi-fi]]
  * [[http://www.sid.unipi.it/polo2/studenti/ | F.A.Q.s about the labs]]
  * [[https://start.unipi.it/help-ict/vpn/ | Unipi VPN ]]
  * [[https://autenticazione.unipi.it/auth/auth.signin | Unipi Authentication]] to access the VPN, make sure that network access services are enabled on your profile. Follow this link to access your Unipi profile.
====== Class calendar - (2024-2025) ======
^ Day  ^ Topic ^ Slides  ^ Data/Software ^ References ^ Video Lectures ^
|18.09| Introduction to the Course. BI Architectures. File data access. | {{ :mds:lbi:2024-lds.01.introduction.pdf | Introduction}} {{ :mds:lbi:2024-lds.02.bi_architectures.pdf | BI architectures}} {{ :mds:lbi:2024-lds.03.file_data_access.pdf | Files}} | |-** BI technology:** [[https://cacm.acm.org/magazines/2011/8/114953-an-overview-of-business-intelligence-technology/fulltext | An Overview of Business Intelligence Technology]] - **File access:** {{ :mds:lbi:filesystem.pdf | File System Interface}} | [[https://unipiit.sharepoint.com/:v:/s/Registrazioni628/EZeGVNiFuYlDq_UbKCecP6gB_kZpwz9DnIPvVoFfLM2laQ?nav=eyJyZWZlcnJhbEluZm8iOnsicmVmZXJyYWxBcHAiOiJTdHJlYW1XZWJBcHAiLCJyZWZlcnJhbFZpZXciOiJTaGFyZURpYWxvZy1MaW5rIiwicmVmZXJyYWxBcHBQbGF0Zm9ybSI6IldlYiIsInJlZmVycmFsTW9kZSI6InZpZXcifX0%3D&e=aaYsXE|video]] |
|25.09| Python Recap. + Exercises | {{ :mds:lbi:2024-lds.04.python.no.ex.sol.pdf | Python Recap (no sol)}} | {{ :mds:lbi:2024-lds.04_supplementary.code.zip | supplementary code}} | | |
|02.10| | | | | |
|09.10| | | | | |
|22.10| | | | | |
|23.10| | | | | |
|30.10| | | | | |
|06.11| | | | | |
|07.11| | | | | |
|12.11| | | | | |
|13.11| | | | | |
|14.11| | | | | |
|19.11| | | | | |
|20.11| | | | | |
|21.11| | | | | |
|03.12| | | | | |
|04.12| | | | | |
|05.12| | | | | |
|10.12| | | | | |
|11.12| | | | | |
|12.12| | | | | |
====== Exams ======

__//There are no mid-terms//.__ 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 with discussion on the topics of the second module (50% of the final grade). See [[mds:dsd:start|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.**

**PROJECT **

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

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

Each part of the project **must be documented** with a brief pdf report (no more than 5 pages) describing your solution.

**Project to be delivered within 27/12/2024 **
  * **Dataset:** 
  
**Project to be delivered during the exam sessions **
Students who did not deliver the above project by 27/12/2024 need to ask by email a new project to the teachers. The project that will be assigned will require about 2 weeks of work. After the delivery, the project will be discussed during the oral exam. For those students, the oral exams will also cover some practical parts that could not be included in the project. ** Please write to all teachers!**


===== Exam sessions =====

Registration to the written exam is mandatory (**pay attention at the deadline for registering!**): [[https://esami.unipi.it/esami2/|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 discussion of the lab project will be communicated to you. The dates at the
[[https://esami.unipi.it/esami2/|registration website]] regard **only** the written part of the DSD module.

=====Past Editions =====
  * [[LDS 2023-2024]]
  * [[LDS 2022-2023]]
  * [[LDS 2021-2022]]
  * [[LDS 2020-2021]]
  * [[LDS 2019-2020]]
  * [[LDS 2018-2019]]
  * [[LBI 2017-2018]]