Differenze

Queste sono le differenze tra la revisione selezionata e la versione attuale della pagina.

--- mds:lbi:start [18/09/2024 alle 21:25 (14 mesi fa)] – [Class calendar - (2024-2025)] Anna Monreale
+++ mds:lbi:start [04/11/2025 alle 11:35 (17 ore fa)] (versione attuale) – Anna Monreale
@@ Linea 1: / Linea 1: @@
-====== Decision Support Systems - Module II (6 ECTS): LABORATORY OF DATA SCIENCE (2024/2025) ======
+====== Decision Support Systems - Module II (6 ECTS): LABORATORY OF DATA SCIENCE (2025/2026) ======
 This is the second module of [[mds:dss:start|Decision Support Systems]] (801AA, 12 ECTS), previously called Laboratory of Data Science (664AA, 6 ECTS).
@@ Linea 8: / Linea 8: @@
     * [[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).
+    * Office hours: Friday: 14:30-15:30 online using Teams or at the Department of Computer Science, room 374/E (Please ask for an appointment by email).
     * Telephone +39-050-2213119
@@ Linea 16: / Linea 16: @@
     * 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.**
+**Always email both instructors and include [LDS] at the beginning of the subject line.**
@@ Linea 22: / Linea 22: @@
 ^  Day of Week  ^  Hour  ^  Room  ^
-|  Tuesday  |  9:00 - 11:00  |  Fib C  |
+| Tuesday | 9:00 - 11:00 | Fib H-Lab |
-|  Wednesday  |  16:00 - 18:00  |  Fib H-Lab  |
+| Wednesday | 11:00 - 13:00 | Fib C1 |
-|  Thursday  |  11:00 - 13:00  |  Fib A1  |
+| Thursday | 11:00 - 13:00 | Fib C |
-|  Friday  |  11:00 - 13:00  |  Fib L1  |
+| Friday | 09:00 - 11:00 | Fib C |
-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.
+A [[https://teams.microsoft.com/l/channel/19%3Aead0080c194243dbabdc9ef2b826d701%40thread.tacv2/Module%20II%20-%20Laboratory%20of%20Data%20Science?groupId=a9d127ae-4a11-4a6b-a045-555d1bab8b85&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 person 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. The recording publication could receive some delays (one week of delays).
 ====== Learning Material ======
@@ Linea 42: / Linea 42: @@
 ===== Software=====
-  * Anaconda (Please avoid Python 3.12)
+  * Anaconda
-  * 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]].
+  * SQL Server 2019 Management Studio or newer:[[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]].
+  * Visual Studio Community 2022. Install/include SSDT workload in the installation manager of Visual Studio: instructions 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]]
+  * [[https://start.unipi.it/help-ict/vpn/ | Unipi VPN ]]
-**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.
+**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 [[http://office.com|office.com]] using your University credentials.
 ===== F.A.Q. =====
@@ Linea 55: / Linea 56: @@
   * [[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) ======
+====== Class calendar - (2025-2026) ======
-^ Day  ^ Topic ^ Slides  ^ Data/Software ^ References ^ Video Lectures ^
+^N. ^ Day  ^Room ^ Topic ^ Slides  ^ Data/Code ^ 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]] |
+|1.|01.10| |Introduction to the Course. BI Architectures. File data access. |{{ :mds:lbi:2025-lds.01.introduction.pdf |}} {{ :mds:lbi:2025-lds.02.bi_architectures.pdf |}} {{ :mds:lbi:2025-lds.03.file_data_access.pdf |}}| |  |
-|25.09| | | | | |
+|3.|02.10| |File data access. Python Recap. | {{ :mds:lbi:2025-lds.04.python_no_hint.pdf | Python Recap}} | {{ :mds:lbi:2024-lds.04_supplementary.code.zip | supplementary code}} |
-|02.10| | | | | |
+|4.|22.10| |Project Presentation + Python Excercises + File Access in Python |{{ :mds:lbi:2025-lds.05.fileaccess-python.pdf |}} | {{ :mds:lbi:2025-10-23-code.zip |}} | |
-|09.10| | | | | |
+|5.|29.10| |Python File Access + Exercises | | same slides used in the previous lecture{{ :mds:lbi:data1.zip | Data ex files}} |  |
-|22.10| | | | | |
+| |30.10| |Lecture canceld |  |  |
-|23.10| | | | | |
+|6.|04.11| |RDBMS access protocols + Python DB Access	 | {{ :mds:lbi:2024-lds.06.relational_data_access.pdf | Slides}}|  | |
-|30.10| | | | | |
+|7.|05.11| |Exercises correction + Stratified sampling Exercise | |  | |
-|06.11| | | | | |
+|8.|13.11| Fib C | | |  | |
-|07.11| | | | | |
+|9.|14.11| Lab H | | |  | |
-|12.11| | | | | |
+|10.|18.11|Lab H | | |  | |
-|13.11| | | | | |
+|11.|19.11|Lab I | | |  | |
-|14.11| | | | | |
+|12.|20.11| Fib C | | |  | |
-|19.11| | | | | |
+|13.|21.11|Lab H  | | |  | |
-|20.11| | | | | |
+|14.|25.11|Lab H  | |  | | |
-|21.11| | | | | |
+|15.|26.11|Lab I  | |  | | |
-|03.12| | | | | |
+|16.|27.11|Fib C   | |  | | |
-|04.12| | | | | |
+|17.|28.11|Lab H |  | |  | |
-|05.12| | | | | |
+|18.|02.12|Lab H | |  | | |
-|10.12| | | | | |
+|19.|03.12|  | |  | |
-|11.12| | | | | |
+|20.|04.12|  | |  | |
-|12.12| | | | | |
+|21.|05.12| Lab H | | |  | |
+|22.|09.12|  | |  | |
+|23.|10.12|  | |  | |
+|24.|11.12|  | |  | |
 ====== 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.**
+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 [[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.**
+The lab project has to be submitted within the specified deadline that will be communicated asap.
+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 OPLAP cube, and reporting.
+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.
+  * Project assignments: {{ :mds:lbi:lds_project_2025-2026.pdf | LDS Project 2025-26}}
+  * Data: [[https://unipiit-my.sharepoint.com/:u:/g/personal/c_landi7_studenti_unipi_it/EZPEZTUo4ZBDqAbPfp3uGXUBFph9TafaN7o4oSlrz6GE6w?e=EZCAYM|Data]]
-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!**
@@ Linea 103: / Linea 109: @@
 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
+**Important:** The date of the discussion of the lab project will be communicated to you by the instructors. The dates reported in the
-[[https://esami.unipi.it/esami2/|registration website]] regard **only** the written part of the DSD module.
+[[https://esami.unipi.it/esami2/|registration website]] refear **only** the written part of the DSD module.
+**Oral Exam Date for LDS during the Winter Sessions:** TBD
 =====Past Editions =====
+  * [[LDS 2024-2025]]
   * [[LDS 2023-2024]]
   * [[LDS 2022-2023]]