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--- mds:dsd:start [13/10/2022 alle 13:38 (24 mesi fa)] – [Class calendar] Salvatore Ruggieri
+++ mds:dsd:start [24/09/2024 alle 07:09 (21 ore fa)] (versione attuale) – Salvatore Ruggieri
@@ Linea 1: / Linea 1: @@
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+====== Decision Support Systems - Module I (6 ECTS): Decision Support Databases A.Y. 2024/25 ======
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-====== Decision Support Systems - Module I (6 ECTS): Decision Support Databases A.Y. 2022/23 ======
 This is the first module of [[mds:dss:start|Decision Support Systems]] (801AA, 12 ECTS), previously called [[mds:dsd:2021|Decision Support Databases]] (662AA, 6 ECTS).
@@ Linea 57: / Linea 5: @@
 The module presents the main approaches to the design and implementation of decision support databases, and the characteristics of business intelligence tools and computer based information systems used to produce summary information to facilitate appropriate decision-making processes and make them more quick and objectives. Specific attention will be paid to themes such as conceptual and logical Data Warehouses design, data analysis using analytic SQL, algorithms for selecting materialized views, data warehouse systems technology (indexes, star query optimization, physical design, query rewrite methods to use materialized views). A part of the course will be dedicated to a collection of case studies.
-<html><!--<p style="color:#FF0000";><b>The server managing video-recordings and SQL Server is DOWN till Monday 23 November.</b></p>--></html>
 =====Instructor=====
@@ Linea 64: / Linea 11: @@
     * [[http://pages.di.unipi.it/ruggieri/]]
     * [[salvatore.ruggieri@unipi.it]]
-    * **Office hours:** Wednesdays h 14:00 - 16:00 or by appointment, at the Department of Computer Science, room 321/DO, or via Teams.
+    * **Office hours:** Tuesdays h 14:00 - 16:00 or by appointment, at the Department of Computer Science, room 321/DO, or via Teams.
-=====Classes=====
+=====Hours and rooms=====
+The following is the timetable of the whole Decision Support Systems course. The two modules span differently over the semester. The first module will take most of the lessons in September-October. The second module will take most of the lessons in November-December.
 ^  Day of Week  ^  Hour  ^  Room  ^
-|  Wednesday  |  11:00 - 13:00  |  Fib C1  |
+|  Tuesday  |  9:00 - 11:00  |  Fib C  |
-|  Thursday  |  14:00 - 16:00  |  Fib M1  |
+|  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 or of the previous years will be made available here for non-attending students.
 =====Mandatory teaching material =====
-  * **[DW]** A. Albano, S. Ruggieri. [[http://fondamentidibasididati.it/wp-content/uploads/2020/11/DWessential-2021-C3-12-21.pdf|Decision Support Databases Essentials]], University of Pisa, 2 December 2021.
+  * **[DW]** A. Albano, S. Ruggieri. [[http://fondamentidibasididati.it/wp-content/uploads/2020/11/DWessential-2023-C21-12-23.pdf|Decision Support Databases Essentials]], University of Pisa, 21 December 2023.
   * **[DB]** A. Albano. [[http://fondamentidibasididati.it/wp-content/uploads/2020/11/DBEssential-2021-C30-11-21.pdf|DB Essentials]] and [[http://fondamentidibasididati.it/wp-content/uploads/2020/11/DBEssential-2020-Soluzioni-C30-11-21.pdf|solutions to exercises]], University of Pisa, 1 December 2020. This is a self-contained excerpt (in English) from the book [[http://fondamentidibasididati.it|Fondamenti di basi di dati]] (in Italian, free download).
-  * Examples of [[http://patterns.di.unipi.it/dsd/DSDsamples.pdf|written exams with solutions]] and [[http://patterns.di.unipi.it/dsd/dsd2020sample.pdf|written exam]].
+  * Examples of {{ :mds:dsd:dsdsampleswithsolutions.pdf | written exams with solutions}} and {{ :mds:dsd:dsdsampleswithoutsolutions.pdf|written exams without solutions}}.
 =====Software=====
@@ Linea 87: / Linea 41: @@
 =====Preliminary program and calendar=====
-  * [[https://esami.unipi.it/programma.php?c=57058&aa=2022|Preliminary program]].
+  * [[https://esami.unipi.it/programma.php?c=61299&aa=2023|Preliminary program]].
-  * [[https://didattica.di.unipi.it/en/master-programme-in-data-science-and-business-informatics/academic-calendar-2022-2023/|Calendar of lessons]].
+  * [[https://didattica.di.unipi.it/en/master-programme-in-data-science-and-business-informatics/academic-calendar-2024-2025/|Calendar of lessons]].
 =====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). The written part consists of open questions, small exercises, and a Data Warehouse design problem. Each question is assigned a grade, summing up to 30 points. Students are admitted to the oral part if they receive a grade of at least 18 points. Oral consists of critical discussion of the written part and of open questions and problem solving on the topics of the course. See [[mds:lbi:start|Module II: Laboratory of Data Science]] for the lab project.
+__//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). The written part consists of open questions, small exercises, and a Data Warehouse design problem. Each question is assigned a grade, summing up to 30 points. Students are admitted to the oral part if they receive a grade of at least 18 points. Oral consists of critical discussion of the written part and of open questions and problem solving on the topics of the course. See [[mds:lbi:start|Module II: Laboratory of Data Science]] for the lab project. **The project of Module II can be discussed only after passing Module I and not later than one year since then.**
-Registration to the written exam is mandatory (**look at the deadline for registering!**): [[https://esami.unipi.it/esami2/|register here]]\\
+Registration to the written exam is mandatory (pay attention at the deadlines!): [[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. The date reported below is for the DSD written exam. The actual date of the discussion of the lab project will be communicated to you by email.**
 ^  Date  ^  Hour  ^  Room  ^  Notes  ^
-|  26/10/2022  |  14:00 - 16:00  | TBA  | [[https://didattica.di.unipi.it/en/appelli-straordinari/|Extra-ordinary exam]] |
+|  6/11/2024  |  9:00 - 11:00  |  Riunioni Ovest, Dept. Computer Science  | [[https://didattica.di.unipi.it/en/appelli-straordinari/|Extra-ordinary exam]] |
-<html>
-<!--
-|  10/09/2021  |  14:00 - 16:00  |  Online |  **Written exam ONLINE only!**  |
-|  27/11/2020  |  14:00 - 16:00  |  Online exam  | [[https://didattica.di.unipi.it/en/appelli-straordinari/|Extra-ordinary exam]] |
--->
-</html>
-=====Teams channel =====
-A [[https://teams.microsoft.com/l/team/19%3aE3in1CcEGzs_W-8NNuQbNkuua_UaPIAzamLvzVNswdw1%40thread.tacv2/conversations?groupId=279299f3-aa07-48b1-8ec6-b2fd1a6d125d&tenantId=c7456b31-a220-47f5-be52-473828670aa1|Teams channel]] will be used to post news, Q&A, and other stuff related to the course.
 =====Class calendar =====
 Lessons will be **NOT** be live-streamed, but recordings of past years are available here for non-attending students.\\
-Recordings and teaching material are **password protected**. Ask the teacher for credentials.\\
 To watch the recordings online, you must be connected to the [[https://start.unipi.it/en/help-ict/vpn/|unipi.it VPN]]. Alternatively, right click on the link and download the whole file, then watch it locally on your device using e.g. [[http://www.videolan.org/vlc/|VLC media player]].
-**2022-01.** //Thursday 15 September 2022, 14-16// **[DW: 1.1-1.2]**  [[http://patterns.di.unipi.it/dsd/video/dsd01_20220915.mp4|rec01 audio-video (.mp4) current year]]
+Slides and other material might be updated **after the classes** to align with actual content of lessons and to correct typos. Be sure to download the updated versions.
-Course overview. Need for Strategic Information. Information Systems in Organizations: Operational and Decision support. Data driven Decision support systems and Business Intelligence applications. From data to information for decision making. Types of data synthesis: Reports, Multidimensional data analysis, Exploratory data analysis.
-**2022-02.** //Wednesday 21 September 2022, 11-13// **[DW: 1.3-1.7]**  [[http://patterns.di.unipi.it/dsd/video/dsd02_20180919.flv|rec02 audio-video (.flv) past years]]
+^ # ^ Date ^ Room ^ Topic ^ Mandatory teaching material ^
+|01| 17/09 9-11 | Fib-C | Course overview. Need for Strategic Information. Information Systems in Organizations: Operational and Decision support. Data driven Decision support systems and Business Intelligence applications.  [[http://131.114.72.230/dsd/video/dsd01_20220915.mp4|rec01 (.mp4)]] | **[DW: 1.1-1.2]**  {{:mds:dsd:dsd01.pdf|slides01 (.pdf)}} |
-The data warehouse (DW) and DW architectures. What to model in a DW: Facts, measures, dimensions and dimensional hierarchies. Examples of data analysis. Exercises on data analysis in SQL.
+|02| 19/09 11-13 | Fib-A1 | The data warehouse (DW) and DW architectures. What to model in a DW: Facts, measures, dimensions and dimensional hierarchies. Examples of data analysis. Exercises on data analysis in SQL.  [[http://131.114.72.230/dsd/video/dsd02_20180919.flv|rec02 (.flv)]] | **[DW: 1.3-1.7]**  {{:mds:dsd:dsd02.pdf|slides02 (.pdf)}} |
+|03| 20/09 11-13 | Fib-L1 | Recalls: the Object Data Model. {{:mds:dsd:dsd03.assignments.pdf|Exercises at home (Assignments I and II) for the lesson 05}}. [[http://131.114.72.230/dsd/video/dsd03_20210921.mp4|rec03 (.mp4)]] | **[DB: 1.1, 2.1-2.5]**  {{:mds:dsd:dsd03.pdf|slides03 (.pdf)}} |
-**2022-03.** //Thursday 22 September 2022, 14-16// **[DB: 1.1, 2.1-2.5]** [[http://patterns.di.unipi.it/dsd/video/dsd03_20210921.mp4|rec03 audio-video (.mp4) past years]]
+|04| 24/09 9-11 | Fib-C | DW modeling. Representation of facts, measures, dimensions, attributes and dimensional hierarchies. Key steps in conceptual design from business questions. How to identify facts, measures, dimensions, dimensional attributes and hierarchies. Examples. {{:mds:dsd:dsd04.assignments.pdf|Exercises at home (University exams) for the lesson 05}}.  [[http://131.114.72.230/dsd/video/dsd04_20170929.flv|rec04 (.flv)]] | **[DW: 2.1]**  {{:mds:dsd:dsd04.pdf|slides04 (.pdf)}} |
+|05| 26/09 11-13 | Fib-A1 | The example of a data model for Master program exams. Presentation and discussion of the Hospital case study.  {{:mds:dsd:dsd05.assignments.pdf|Exercises at home (Assignment III) for the lesson 07}}.  [[http://131.114.72.230/dsd/video/dsd05_20210928.mp4|rec05 (.mp4)]] | **[DW: 2.1, A.1]**  {{:mds:dsd:dsd05.pdf|slides05 (.pdf)}} |
-Recalls: the Object Data Model. [[http://patterns.di.unipi.it/dsd/dsd.03.assignments.pdf|Exercises at home (Assignments I and II) for the lesson 2022-05]].
+|06| 27/09 11-13 | Fib-C1 | Recalls: the relational model and relational algebra. Exercises. {{:mds:dsd:dsd06.assignments.pdf|Exercises at home (Assignment IV) for the lesson 08}}. [[http://131.114.72.230/dsd/video/dsd06_20211001.mp4|rec06 (.mp4)]] | **[DB: 3.1-3.2]**  {{:mds:dsd:dsd06.pdf|slides06 (.pdf)}} |
+|07| 01/10 9-11 | Fib-C | More about data mart conceptual design, changing dimensions and advanced data model features. From Conceptual design to relational logical design. Star model, snowflake, and constellation. Logical schema of the Hospital case study. {{:mds:dsd:dsd07.assignments.pdf|Exercises at home (Travel agency) for the lesson 09}}.  [[http://131.114.72.230/dsd/video/dsd07_20211005.mp4|rec07 (.mp4)]] | **[DW: 2.1, 2.2, A.1, B.1]**  {{:mds:dsd:dsd07.pdf|slides07 (.pdf)}} |
-**2022-04.** //Wednesday 28 September 2022, 11-13// **[DW: 2.1]**  [[http://patterns.di.unipi.it/dsd/video/dsd04_20170929.flv|rec04 audio-video (.flv) past years]]
+|08| 03/10 11-13 | Fib-A1 | Recalls: the relational model and relational algebra. Logical trees. {{:mds:dsd:dsd08.jrsexercises.pdf|Exercises with JRS}}.  {{:mds:dsd:dsd08.assignments.pdf|Exercises at home (Airline companies) for the lesson 09}}. [[http://131.114.72.230/dsd/video/dsd08_20211008.mp4|rec08 (.mp4)]] | **[DB: 3.2-3.4]**  {{:mds:dsd:dsd08.pdf|slides08 (.pdf)}} |
+|09| 04/10 11-13 | Fib-C1 | Discussion of students' solutions of conceptual and logical design case studies.   [[http://131.114.72.230/dsd/video/dsd09_20211012.mp4|rec09 (.mp4)]] | **[DW: A.2, B.2]**  {{:mds:dsd:dsd09.pdf|slides09 (.pdf)}} |
-DW modeling. A conceptual multidimensional data model. Representation of Fact, measures, dimensions, attributes and dimensional hierarchies. Key steps in conceptual design from business questions. How to identify fact types and fact granularity and measure types. How to identify dimensions, dimensional attributes and hierarchies. Examples.
+|10| 8/10 11-13 | Fib-A1 | Data Warehouse design approaches. Data mart logical design.  [[http://131.114.72.230/dsd/video/dsd10_20211015.mp4|rec08 (.mp4)]] | **[DW: 3.1-3.5]**  {{:mds:dsd:dsd10.pdf|slides10 (.pdf)}} |
-[[http://patterns.di.unipi.it/dsd/dsd.04.assignments.pdf|Exercises at home (University exams) for the lesson 2022-05]].
+|11| 15/10 11-13 | Fib-A1 | Slowly changing dimensions, fast changing dimensions, shared dimensions. Recursive hierarchies. Multivalued dimensions. {{:mds:dsd:dsd11.assignments.pdf|Exercises at home (Travel agency extended) for the lesson 12}}.   [[http://131.114.72.230/dsd/video/dsd11_20221020.mp4|rec09 (.mp4)]] | **[DW: 3.1-3.5]**  {{:mds:dsd:dsd11.pdf|slides11 (.pdf)}} |
+|12| 16/10 16-18 | Fib-H | A DW to support Analytical CRM Analysis. Wrap up on DW design.  {{:mds:dsd:dsd12.assignments.pdf|Exercises at home for the lesson 14}}. [[http://131.114.72.230/dsd/video/dsd12_20211022.mp4|rec12 (.mp4)]] | **[DW: 4.1-4.8]**  {{:mds:dsd:dsd12.pdf|slides12 (.pdf)}} |
-**2022-05.** //Thursday 29 September 2022, 14-16// **[DW: 2.1, A.1]**  [[http://patterns.di.unipi.it/dsd/video/dsd05_20210928.mp4|rec05 audio-video (.mp4) past years]]
+|13| 17/10 11-13 | Fib-A1 | Multidimensional Cube model: OLAP Operations. The extended cube and the lattice of cuboids. Pivot tables in Excel. [[http://131.114.72.230/dsd/video/dsd13a_20231107.mp4|rec13a (.mp4)]] and [[http://131.114.72.230/dsd/video/dsd13b_20211026.mp4|rec13b (.mp4)]] **Additional learning material:** G. Harvey. Excel 2013 All-in-One For Dummies, 2013. [[http://131.114.72.230/dsd/PivotTable2013BookVIIchpt2.pdf|Chp. VII-2]] and [[http://131.114.72.230/dsd/HerbalTeas.xlsx|example data for pivot table]]. | **[DW: 2.3, 2.4]**  {{:mds:dsd:dsd13.pdf|slides13 (.pdf)}} |
+|14| 18/10 11-13 | Fib-C1 | Recalls on: DBMS, from SQL to extended relational algebra. Exercises. {{:mds:dsd:dsd14.assignments.pdf|Exercises at home for the lesson 15}}. [[http://131.114.72.230/dsd/video/dsd14_20221102.mp4|rec14 (.mp4)]] | **[DB: 4.1-4.2,5.1-5.11]**  {{:mds:dsd:dsd14.pdf|slides14 (.pdf)}} |
-The example of a data model for Master program exams. Presentation and discussion of the Hospital case study.  [[http://patterns.di.unipi.it/dsd/dsd.05.assignments.pdf|Exercises at home (Assignment III) for the lesson 2022-07]].
+|15| 24/10 11-13 | Fib-A1 | OLAP systems. Data Analysis Using SQL. Simple reports. Examples. Moderately Difficult Reports. Solutions in SQL. {{:mds:dsd:dsd15.foodmart.pdf|Foodmart datawarehouse schema}}. [[http://131.114.72.230/dsd/video/dsd15_20211102.mp4|rec15 (.mp4)]] | **[DW: 5.1-5.3]**  {{:mds:dsd:dsd15.pdf|slides15 (.pdf)}} |
+|16| 25/10 11-13 | Fib-C1 | Examples of variance reports. Very Difficult Reports without Analytic SQL. Example of reports with ranks. Analytic Functions with the use of partitions and running totals. Examples.  {{:mds:dsd:dsd16.assignments.pdf|Exercises at home for the lesson 17}}. [[http://131.114.72.230/dsd/video/dsd16_20211105.mp4|rec16 (.mp4)]] | **[DW: 5.4-5.5]**  {{:mds:dsd:dsd16.pdf|slides16 (.pdf)}} |
-**2022-06.** //Wednesday 5 October 2022, 11-13// **[DB: 3.1-3.2]**  [[http://patterns.di.unipi.it/dsd/video/dsd06_20211001.mp4|rec06 audio-video (.mp4) past years]]
+|17| 31/10 11-13 | Fib-A1 | Analytic Functions with the use of moving windows. Examples. Exercises on Analytic SQL. {{:mds:dsd:dsd17.assignments.pdf|Exercises during the lesson and at home}} and [[http://131.114.72.230/dsd/dsd.17.solutions.txt|solutions]]. [[http://131.114.72.230/dsd/video/dsd17_20211109.mp4|rec17 (.mp4)]] | **[DW: 5.5-5.6]**  {{:mds:dsd:dsd17.pdf|slides17 (.pdf)}} |
+|18| 05/11 9-11 | Fib-C | Recalls of relational DBMS internals: Storage, Indexing and Query Evaluation. Physical operators and physical plans for projection, selection, joins and grouping. Examples. [[http://131.114.72.230/dsd/video/dsd18_20211112.mp4|rec18 (.mp4)]] | **[DB: 6.1-6.6, 6.8, 7.1-7.2]**  {{:mds:dsd:dsd18.pdf|slides18 (.pdf)}} |
-Recalls: the relational model and relational algebra. Exercises.
+|19| 07/11 11-13 | Fib-A1 | Data Warehouse Systems: Special-Purpose Indexes and Star Query Plan. Bitmap indexes. Join indexes. Star queries optimization and query plans. Examples. Table partitioning. [[http://131.114.72.230/dsd/video/dsd19_20211116.mp4|rec19 (.mp4)]] | **[DW: 6.1-6.4]**  {{:mds:dsd:dsd19.pdf|slides19 (.pdf)}} |
-[[http://patterns.di.unipi.it/dsd/dsd.06.assignments.pdf|Exercises at home (Assignment IV) for the lesson 2022-08]].
+|20| 08/11 11-13 | Fib-C1 | The problem of materialized views selection. The lattice of views and the greedy algorithm HRU for the selection of materialized views. Examples. Other algorithms for the choice of the views to materialize with a workload and dimensional hierarchies.  {{:mds:dsd:dsd20.assignments.pdf|Exercises at home for the lesson 21}}. [[http://131.114.72.230/dsd/video/dsd20_20211119.mp4|rec20 (.mp4)]] | **[DW: 7.1-7.7]**  {{:mds:dsd:dsd20.pdf|slides20 (.pdf)}} |
+|21| 15/11 11-13 | Fib-C1 | Recalls of functional dependency properties and how they are used to reason about the properties of the result of a query. Properties of the group-by operator.   [[http://131.114.72.230/dsd/video/dsd21_20221130.mp4|rec21 (.mp4)]] | **[DW: 8.1-8.2, DB: 3.5.1-3.5.4]**  {{:mds:dsd:dsd21.pdf|slides21 (.pdf)}} |
-**2022-07.** //Thursday 6 October 2022, 14-16// **[DW: 2.1, 2.2, A.1, B.1]** [[http://patterns.di.unipi.it/dsd/video/dsd07_20211005.mp4|rec07 audio-video (.mp4) past years]]
+|22| 22/11 11-13 | Fib-C1 | The problem of evaluating the group-by before the join operator. First case: Invariant grouping. Examples. Other cases: double grouping, grouping and counting. Examples with star queries.  [[http://131.114.72.230/dsd/video/dsd22_20221201.mp4|rec22 (.mp4)]] | **[DW: 8.3-8.6]**  {{:mds:dsd:dsd22.pdf|slides22 (.pdf)}} |
+|23| 29/11 11-13 | Fib-C1 | The problem of query rewrite to use a materialized view. Hypothesis and two approaches: With a compensation on the logical view plan, and with a transformation of logical query plan. Examples. [[http://131.114.72.230/dsd/video/dsd23_20211130.mp4|rec23 (.mp4)]] | **[DW: 9.1-9.4]**  {{:mds:dsd:dsd23.pdf|slides23 (.pdf)}} |
-More about data mart conceptual design, changing dimensions and advanced data model features. From Conceptual design to relational logical design. Star model, snowflake, and constellation. Logical schema of the Hospital case study. [[http://patterns.di.unipi.it/dsd/dsd.07.assignments.pdf|Exercises at home (Travel agency) for the lesson 2022-09]].
+|24| 6/12 11-13 | Fib-C1 | Data Warehousing trends: column-oriented DW, main-memory DW, Big Data framework. [[http://131.114.72.230/dsd/video/dsd24_20211203.mp4|rec24 (.mp4)]] | **[DW: 6.5-6.8]**  {{:mds:dsd:dsd24.pdf|slides24 (.pdf)}} |
-**2022-08.** //Wednesday 12 October 2022, 11-13//  **[DB: 3.2-3.4]** [[http://patterns.di.unipi.it/dsd/video/dsd08_20211008.mp4|rec08 audio-video (.mp4) past years]]
-Recalls: the relational model and relational algebra. Logical trees. [[http://patterns.di.unipi.it/dsd/dsd.08.exercises.pdf|Exercises with JRS]].  [[http://patterns.di.unipi.it/dsd/dsd.08.assignments.pdf|Exercises at home (Airline companies) for the lesson 2022-09]].
-**2022-09.** //Thursday 13 October 2022, 14-16// **[DW: A.2, B.2]** [[http://patterns.di.unipi.it/dsd/video/dsd09_20211012.mp4|rec09 audio-video (.mp4) past years]]
-Discussion of students' solutions of conceptual and logical design case studies.
-**2022-10.** //Wednesday 19 October 2022, 11-13// **[DW: 3.1-3.5]** [[http://patterns.di.unipi.it/dsd/video/dsd10_20211015.mp4|rec10 audio-video (.mp4)]]
-Data Warehouse design approaches. Data mart logical design.
-**2022-11.** //Thursday 20  October 2022, 14-16// **[DW: 3.1-3.5]**[[http://patterns.di.unipi.it/dsd/video/dsd11_20211019.mp4|rec11 audio-video (.mp4)]]
-Slowly changing dimensions, fast changing dimensions, shared dimensions. Recursive hierarchies. Multivalued dimensions. [[http://patterns.di.unipi.it/dsd/dsd.11.assignments.pdf|Exercises at home (Travel agency extended) for the lesson 2022-12]].
-**2022-12.** //Wednesday 26 October 2022, 11-13//
-...
-=====Class calendar previous A. Y. =====
-**2021-12.** //Friday 22 October 2021, 16-18// **[DW: 4.1-4.8]** [[http://patterns.di.unipi.it/dsd/video/dsd12_20211022.mp4|rec12 audio-video (.mp4)]]
-A DW to support Analytical CRM Analysis. Wrap up on DW design.  [[http://patterns.di.unipi.it/dsd/dsd.12.assignments.pdf|Exercises at home for the lesson 2021-14]].
-**2021-13.** //Tuesday 26 October 2021, 9-11// **[DW: 2.3, 2.4]**[[http://patterns.di.unipi.it/dsd/video/dsd13_20211026.mp4|rec13 audio-video (.mp4)]]
-Multidimensional Cube model: OLAP Operations. The extended cube and the lattice of cuboids. Pivot tables in Excel. PowerPivot.\\
-**Additional learning material:**
-  * G. Harvey. Excel 2013 All-in-One For Dummies, 2013. [[http://patterns.di.unipi.it/dsd/PivotTable2013BookVIIchpt2.pdf|Chp. VII-2]] and [[http://patterns.di.unipi.it/dsd/HerbalTeas.xlsx|example data for pivot table]].
-  * [[https://support.office.com/en-us/article/power-pivot-overview-and-learning-f9001958-7901-4caa-ad80-028a6d2432ed|Power Pivot overview]].
-**2021-14.** //Friday 29 October 2021, 16-18// **[DB: 4.1-4.2,5.1-5.11]** [[http://patterns.di.unipi.it/dsd/video/dsd14_20211029.mp4|rec14 audio-video (.mp4)]]
-Recalls on: DBMS, from SQL to extended relational algebra. Exercises.
-[[http://patterns.di.unipi.it/dsd/dsd.14.assignments.pdf|Exercises at home for the lesson 2021-15]].
-**2021-15.** //Tuesday 2 November 2021, 9-11//  **[DW: 5.1-5.3]** [[http://patterns.di.unipi.it/dsd/video/dsd15_20211102.mp4|rec15 audio-video (.mp4)]]
-OLAP systems. Data Analysis Using SQL. Simple reports. Examples. Moderately Difficult Reports. Solutions in SQL.
-[[http://patterns.di.unipi.it/dsd/dsd.15.foodmart.pdf|Foodmart datawarehouse schema]].
-**2021-16.** //Friday 5 November 2021, 16-18// **[DW: 5.4-5.5]** [[http://patterns.di.unipi.it/dsd/video/dsd16_20211105.mp4|rec16 audio-video (.mp4)]]
-Examples of variance reports. Very Difficult Reports without Analytic SQL. Example of reports with ranks. Analytic Functions with the use of partitions and running totals. Examples.  [[http://patterns.di.unipi.it/dsd/dsd.16.assignments.pdf|Exercises at home for the lesson 2021-17]].
-**2021-17.** //Tuesday 9 November 2021, 9-11//  **[DW: 5.5-5.6]** [[http://patterns.di.unipi.it/dsd/video/dsd17_20211109.mp4|rec17 audio-video (.mp4)]]
-Analytic Functions with the use of moving windows. Examples. Exercises on Analytic SQL. [[http://patterns.di.unipi.it/dsd/dsd.17.assignments.pdf|Exercises during the lesson and at home]] and [[http://patterns.di.unipi.it/dsd/dsd.17.solutions.txt|solutions]].
-**2021-18.** //Friday 12 November 2021, 16-18// **[DB: 6.1-6.6, 6.8, 7.1-7.2]** [[http://patterns.di.unipi.it/dsd/video/dsd18_20211112.mp4|rec18 audio-video (.mp4)]]
-Recalls of relational DBMS internals: Storage, Indexing and Query Evaluation. Physical operators and physical plans for projection, selection, joins and grouping. Examples.
-**2021-19.** //Tuesday 16 November 2021, 9-11// **[DW: 6.1-6.4]** [[http://patterns.di.unipi.it/dsd/video/dsd19_20211116.mp4|rec19 audio-video (.mp4)]]
-Data Warehouse Systems: Special-Purpose Indexes and Star Query Plan. Bitmap indexes. Join indexes. Star queries optimization and query plans. Examples. Table partitioning.
-**2021-20.** //Friday 19 November 2021, 16-18// **[DW: 7.1-7.7]**[[http://patterns.di.unipi.it/dsd/video/dsd20_20211119.mp4|rec20 audio-video (.mp4)]]
-The problem of materialized views selection. The lattice of views and the greedy algorithm HRU for the selection of materialized views. Examples. Other algorithms for the choice of the views to materialize with a workload and dimensional hierarchies.  [[http://patterns.di.unipi.it/dsd/dsd.20.assignments.pdf|Exercises at home for the lesson 2021-21]].
-**2021-21.** //Tuesday 23 November 2021, 9-11//  **[DW: 8.1-8.2, DB: 3.5.1-3.5.4]** [[http://patterns.di.unipi.it/dsd/video/dsd21_20211123.mp4|rec21 audio-video (.mp4)]]
-Recalls of functional dependency properties and how they are used to reason about the properties of the result of a query. Properties of the group-by operator.
-**2021-22.** //Friday 26 November 2021, 16-18// **[DW: 8.3-8.6]** [[http://patterns.di.unipi.it/dsd/video/dsd22_20211126.mp4|rec22 audio-video (.mp4)]]
-The problem of evaluating the group-by before the join operator. First case: Invariant grouping. Examples. Other cases: double grouping, grouping and counting. Examples with star queries.
-**2021-23.** //Tuesday 30 November 2021, 9-11// **[DW: 9.1-9.4]** [[http://patterns.di.unipi.it/dsd/video/dsd23_20211130.mp4|rec23 audio-video (.mp4)]]
-The problem of query rewrite to use a materialized view. Hypothesis and two approaches: With a compensation on the logical view plan, and with a transformation of logical query plan. Examples.
-**2021-24.** //Friday 3 December 2021, 16-18// **[DW: 6.5-6.8]**  [[http://patterns.di.unipi.it/dsd/video/dsd24_20211203.mp4|rec24 audio-video (.mp4)]]
-Data Warehousing trends: column-oriented DW, main-memory DW, Big Data framework.
 =====Previous years=====
+  * [[mds:dsd:2023|Decision Support Databases  A.Y. 2023/24]]
+  * [[mds:dsd:2022|Decision Support Databases  A.Y. 2022/23]]
   * [[mds:dsd:2021|Decision Support Databases  A.Y. 2021/22]]
+  * [[mds:dsd:2020|Decision Support Databases  A.Y. 2020/21]] (special edition)