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mds:dsd:start [22/05/2019 alle 11:57 (5 anni fa)]
Salvatore Ruggieri [Instructor]
mds:dsd:start [27/03/2024 alle 13:18 (29 ore fa)] (versione attuale)
Salvatore Ruggieri [Exams]
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-====== Decision Support Databases A.Y. 2018/19 ======+====== Decision Support Systems - Module I (6 ECTS): Decision Support Databases A.Y. 2023/24 ======
  
-The course presents the main approaches to the design and implementation of decision support databasesand 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. Particular attention will be paid to themes such as conceptual and logical Data Warehouses designdata analysis using analytic SQL, algorithms for selecting materialized views, data warehouse systems technology (indexesstar 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.+This is the first module of [[mds:dss:start|Decision Support Systems]] (801AA12 ECTS)previously called [[mds:dsd:2021|Decision Support Databases]] (662AA6 ECTS). 
  
 +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===== =====Instructor=====
  
-  * **Salvatore Ruggieri** (Lectures)+  * **Salvatore Ruggieri** 
     * Università di Pisa     * Università di Pisa
     * [[http://pages.di.unipi.it/ruggieri/]]     * [[http://pages.di.unipi.it/ruggieri/]]
-    * [[ruggieri@di.unipi.it]]   +    * [[salvatore.ruggieri@unipi.it]]   
-    * **Office hours:** Tuesdays h 14:00 - 17:00 or by appointment, Department of Computer Science, room 321/DO.+    * **Office hours:** Tuesdays h 14:00 - 16:00 or by appointment, at the Department of Computer Science, room 321/DO, or via Teams.
  
-<html> 
-<!--<p style="color:#FF0000";>Office hours on 21 May 2019 will be at 16-18.</p>--> 
-</html> 
-  
  
-=====Classes=====+=====Hours and rooms=====
  
-Lessons will be held atPolo Didattico "L. Fibonacci", Via F. Buonarroti 4, Pisa.\\+^  Day of Week  ^  Hour  ^  Room  ^  
 +|  Wednesday  |  11:00 - 13:00  |  Fib L1  | 
 +|  Thursday  |  14:00 - 16:00  |  Fib L1  |
  
-^  Day of Week  ^  Hour  ^  Room  ^  Type  ^  
-|  Thursday |  16:00 - 18:00  |  Fib C1  |  Lectures  | 
-|  Friday|  16:00 - 18:00  |  Fib A1  |  Lectures  | 
  
 +A [[https://teams.microsoft.com/l/channel/19%3a16c4847872b34df2bfe2e0097597c330%40thread.tacv2/Module%2520I%2520-%2520Decision%2520Support%2520Databases?groupId=6bc87f32-e2c1-46b8-9c9f-928cae8bbe4d&tenantId=c7456b31-a220-47f5-be52-473828670aa1|Teams channel]] is used ONLY 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 =====
  
-=====Mandatory teaching material===== +  * **[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 2020This is a self-contained excerpt (in English) from the book [[http://fondamentidibasididati.it|Fondamenti di basi di dati]] (in Italianfree download)
-  * **[DW]** A. Albano, S. Ruggieri. [[http://apa.di.unipi.it/bsd/DWEssentialsWithoutSolutions.pdf|Decision Support Databases Essentials]], University of Pisa, 2017.  +  * Examples of {{ :mds:dsd:dsdsamples.pdf | written exams with solutions}} and [[http://131.114.72.230/dsd/dsd2020sample.pdf|written exam]]. 
-  * **[DWSol]** A. Albano, SRuggieriDecision Support Databases Essentials[[http://apa.di.unipi.it/bsd/DWEssentialsSolutions.pdf|Solutions to Case Studies]], University of Pisa, 2017.  +=====Software=====
-  * **[DB]** A. Albano. [[http://apa.di.unipi.it/bsd/DBEssentials.pdf|Databases Essentials]], University of Pisa, 2016+
-  * Examples of [[http://apa.di.unipi.it/bsd/BSDsamples.pdf|written exams with solutions]].+
  
 +  * [[http://fondamentidibasididati.it/index.php/download/|JRS]] for practicing with logical and physical SQL query plans. JRS requires [[https://www.oracle.com/java/technologies/downloads/#java8|Java SE Runtime Environment 8u341]] (need to register to download)
 +  * [[https://docs.microsoft.com/en-us/sql/azure-data-studio/download|Azure Data Studio]] or [[https://docs.microsoft.com/en-us/sql/ssms/download-sql-server-management-studio-ssms|SQL Server Management Studio]] client for connecting to SQL Server DBMS Foodmart database
 +  * [[https://start.unipi.it/en/help-ict/vpn/|Access to University digital services through VPN]] connect to unipi VPN (unless you are already in the unipi.it network) for accessing the Foodmart database
  
 =====Preliminary program and calendar===== =====Preliminary program and calendar=====
  
-  * [[https://esami.unipi.it/esami2/programma.php?c=37347&aa=2018|Preliminary program]]. +  * [[https://esami.unipi.it/programma.php?c=61299&aa=2023|Preliminary program]]. 
-  * [[https://www.di.unipi.it/en/education/mds/academic-calendar-2018-2019-wds|Calendar of lessons]].+  * [[https://didattica.di.unipi.it/en/master-programme-in-data-science-and-business-informatics/academic-calendar-2023-2024/|Calendar of lessons]].
  
  
 =====Exams===== =====Exams=====
  
-__//There are no mid-terms//.__ The exam consists of a written part and an oral part. 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.  +__//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. Module I and Module II must be passed at maximum distance of one year between them (they can be taken in any order).
-Registration to exams is mandatory: [[https://esami.unipi.it/esami2/|register here]]+
  
-^  Date  ^  Hour  ^  Room  ^   +Registration to the written exam is mandatory (**pay attention at the deadline for registering!**)[[https://esami.unipi.it/esami2/|register here]]\\
-|  18/6/2019  |  16:00 - 18:00  |  Fib-N1 +
-|  2/7/2019  |  9:00 - 11:00  |  Fib-L1 +
-|  24/7/2019  |  9:00 - 11:00  |  Fib-L1  | +
-=====Class calendar=====+
  
-Recordings are password protected. Ask the teacher for credentials.+**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  ^
 +|  28/5/2024  |  9:00 - 11:00  |  TBD  |    |
 +|  25/6/2024  |  9:00 - 11:00  |  TBD  |    |
 +|  23/7/2024  |  9:00 - 11:00  |  TBD  |    |
 +|  13/9/2024  |  11:00 - 13:00  |  TBD  |    |
  
-**01.** //Monday 17 September 2018, 14-16// **[DW: 1.1-1.2]** [[http://apa.di.unipi.it/bsd/video/rec01_20170918.flv|Recording (past years)]]+<html> 
 +<!-- [[https://didattica.di.unipi.it/en/appelli-straordinari/|Extra-ordinary exam]] --> 
 +</html>
  
-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. +=====Class calendar =====
-  +
  
-**02.** //Wednesday 19 September 20189-11// **[DW: 1.3-1.7]** [[http://apa.di.unipi.it/bsd/video/rec02_20180919.flv|Recording (current year)]]+Lessons will be **NOT** be live-streamedbut recordings of past years are available here for non-attending students.\\
  
-The data warehouse (DW) and DW architectures. What to model in a DW: Facts, measures, dimensions and dimensional hierarchies. Examples of data analysisExercises on data analysis in SQL.+Some of recordings and teaching material are **password protected**Ask the teacher for credentials.\\
  
-**03.** //Thursday 27 September 2018, 16-18// **[DB: 1.12.1-2.5]** [[http://apa.di.unipi.it/bsd/video/rec03_20170925.flv|Recording (past years)]]+To watch the recordings online, you must be connected to the [[https://start.unipi.it/en/help-ict/vpn/|unipi.it VPN]]. Alternativelyright 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]].
  
-Recallsthe Object Data Model.+**2023-01.** //Wednesday 20 September 2023, 11-13// **[DW1.1-1.2]** [[http://131.114.72.230/dsd/video/dsd01_20220915.mp4|rec01 audio-video (.mp4) past years]]
  
-**04.** //Friday 28 September 2018, 16-18// **[DW: 2.1]** [[http://apa.di.unipi.it/bsd/video/rec04_20170929.flv|Recording (past years)]]+Course overviewNeed for Strategic InformationInformation Systems in OrganizationsOperational and Decision supportData driven Decision support systems and Business Intelligence applicationsFrom data to information for decision makingTypes of data synthesis: Reports, Multidimensional data analysis, Exploratory data analysis.
  
-DW modelingA conceptual multidimensional data model. Representation of Fact, measuresdimensions, 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.\\ +**2023-02.** //Thursday 21 September 202314-16// **[DW1.3-1.7]**  [[http://131.114.72.230/dsd/video/dsd02_20180919.flv|rec02 audio-video (.flv) past years]]
-**Slides:** [[http://apa.di.unipi.it/bsd/UniversityCaseStudy.pdf|university requirements]].+
  
-**05.** //Thursday 4 October 2018, 16-18// **[DW: 2.1A.1]** [[http://apa.di.unipi.it/bsd/video/rec05_20171002.flv|Recording (past years)]]+The data warehouse (DW) and DW architecturesWhat to model in a DW: Factsmeasures, dimensions and dimensional hierarchiesExamples of data analysisExercises on data analysis in SQL.
  
-The example of a data model for Master program examsPresentation and discussion of the Hospital case study.+**2023-03.** //Wednesday 27 September 2023, 11-13// **[DB: 1.1, 2.1-2.5]** [[http://131.114.72.230/dsd/video/dsd03_20210921.mp4|rec03 audio-video (.mp4) past years]]
  
-**06.** //Friday 5 October 2018, 16-18// **[DB3.1-3.2]** [[http://apa.di.unipi.it/bsd/video/rec06_20181005.flv|Recording (current year)]]+Recallsthe Object Data Model. [[http://131.114.72.230/dsd/dsd.03.assignments.pdf|Exercises at home (Assignments I and IIfor the lesson 2023-05]].
  
-Recallsthe relational model and relational algebraExercises.+**2023-04.** //Thursday 28 September 2023, 14-16// **[DW2.1]**  [[http://131.114.72.230/dsd/video/dsd04_20170929.flv|rec04 audio-video (.flv) past years]]
  
-**07.** //Thursday 11 October 2018, 16-18// **[DW: 2.1,2.2,A.1]** [[http://apa.di.unipi.it/bsd/video/rec07_20181011.flv|Recording (current year)]]+DW modelingA conceptual multidimensional data modelRepresentation of Factmeasures, dimensions, attributes and dimensional hierarchies. Key steps in conceptual design from business questionsHow to identify fact types and fact granularity and measure types. How to identify dimensionsdimensional attributes and hierarchies. Examples. 
 +[[http://131.114.72.230/dsd/dsd.04.assignments.pdf|Exercises at home (University examsfor the lesson 2023-05]].
  
-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. 
  
-**XX** <del>//Friday 12 October 201816-18//</del> +**2023-05.** //Wednesday 4 October 202311-13// **[DW: 2.1, A.1]**  [[http://131.114.72.230/dsd/video/dsd05_20210928.mp4|rec05 audio-video (.mp4) past years]]
  
-Lesson canceled to allow students' participation to the [[https://www.internetfestival.it/|Internet Festival]]. It will be recovered in November.+The example of a data model for Master program exams. Presentation and discussion of the Hospital case study.  [[http://131.114.72.230/dsd/dsd.05.assignments.pdf|Exercises at home (Assignment III) for the lesson 2023-07]].
  
-**08.** //Thursday 18 October 201816-18// **[DB: 3.2-3.3]** [[http://apa.di.unipi.it/bsd/video/rec08_20171016.flv|Recording (past years)]]+**2023-06.** //Thursday October 202314-16// **[DB: 3.1-3.2]**  [[http://131.114.72.230/dsd/video/dsd06_20211001.mp4|rec06 audio-video (.mp4) past years]]
  
-Recalls: the relational model and relational algebra. Logical trees. Exercises.+Recalls: the relational model and relational algebra. Exercises.  
 +[[http://131.114.72.230/dsd/dsd.06.assignments.pdf|Exercises at home (Assignment IV) for the lesson 2023-08]].
  
-**09.** //Friday 19 October 201816-18// **[DW: 2.3,2.4]** [[http://apa.di.unipi.it/bsd/video/rec09_20181019.flv|Recording (current year)]]+**2023-07.** //Wednesday 11 October 202311-13//**[DW: 2.1, 2.2, A.1, B.1]** [[http://131.114.72.230/dsd/video/dsd07_20211005.mp4|rec07 audio-video (.mp4past years]]
  
-Multidimensional Cube model: OLAP OperationsThe extended cube and the lattice of cuboids. Pivot tables in Excel. PowerPivot.\\ +More about data mart conceptual design, changing dimensions and advanced data model features. From Conceptual design to relational logical designStar model, snowflake, and constellation. Logical schema of the Hospital case study. [[http://131.114.72.230/dsd/dsd.07.assignments.pdf|Exercises at home (Travel agencyfor the lesson 2023-09]].
-**Additional learning material:** +
-  * G. Harvey. Excel 2013 All-in-One For Dummies, 2013. [[http://apa.di.unipi.it/bsd/PivotTable2013BookVIIchpt2.pdf|ChpVII-2]] and [[http://apa.di.unipi.it/bsd/HerbalTeasCube.xlsx|example pivot table]]. +
-  * [[https://msdn.microsoft.com/en-us/library/gg399183(v=sql.110).aspx|Power Pivot manual]].+
  
-**XX** <del>//Thursday 25 October 2018, 16-18//</del> +**2023-08.** //Thursday 12 October 202314-16// **[DB: 3.2-3.4]** [[http://131.114.72.230/dsd/video/dsd08_20211008.mp4|rec08 audio-video (.mp4) past years]]
  
-Lesson canceled due to institutional duties of the teacherIt will be recovered in November.+Recalls: the relational model and relational algebraLogical trees. [[http://131.114.72.230/dsd/dsd.08.exercises.pdf|Exercises with JRS]].  [[http://131.114.72.230/dsd/dsd.08.assignments.pdf|Exercises at home (Airline companies) for the lesson 2023-09]].
  
-**XX** <del>//Friday 26 October 2018, 16-18//</del>  
  
-Lesson canceled due to institutional duties of the teacherIt will be recovered in November.+**2023-09.** //Wednesday 18 October 2023, 11-13// **[DW: A.2, B.2]** [[http://131.114.72.230/dsd/video/dsd09_20211012.mp4|rec09 audio-video (.mp4) past years]]
  
-**10.** //Thursday 8 November 2018, 16-18// **[DW: A.2,3.1-3.5], [DWSol: B.2]** [[http://apa.di.unipi.it/bsd/video/rec10_20171023.flv|Recording (past years)]]+Discussion of students' solutions of conceptual and logical design case studies 
  
-Discussion of students' solutions of conceptual and logical design case studiesThe airline companiesA Data Warehouse Design MethodologyApproachesDesign phasesRequirements specifications.+**2023-10.** //Thursday 19 October 2023, 14-16// **[DW: 3.1-3.5]** [[http://131.114.72.230/dsd/video/dsd10_20211015.mp4|rec10 audio-video (.mp4) past years]]
  
-**11.** //Friday 9 November 2018, 16-18// **[DW: 3.1-3.5]** [[http://apa.di.unipi.it/bsd/video/rec11_20171027.flv|Recording (past years)]]+Data Warehouse design approachesData mart logical design
  
-Data mart logical designSlowly changing dimensionsfast changing dimensionsshared dimensionsRecursive hierarchiesMultivalued dimensionsMultivalued Dimensional Attributes.+**2023-11.** //**Tuesday 24  October 202214-16Room L1**// **[DW: 3.1-3.5]** [[http://131.114.72.230/dsd/video/dsd11_20221020.mp4|rec11 audio-video (.mp4) past years]]
  
-**12.** //Thursday 15 November 201816-18// **[DB: 3.4][DW: 4.1-4.8]** [[http://apa.di.unipi.it/bsd/video/rec12_20181115.flv|Recording (current year)]]+Slowly changing dimensionsfast changing dimensionsshared dimensionsRecursive hierarchies. Multivalued dimensions. [[http://131.114.72.230/dsd/dsd.11.assignments.pdf|Exercises at home (Travel agency extendedfor the lesson 2023-12]].
  
-Recalls on: ODM-to-Relational MappingDW to support Analytical CRM Analysis +**2023-12.** //Thursday 2 November 2023, 14-16//  **[DW: 4.1-4.8]** [[http://131.114.72.230/dsd/video/dsd12_20211022.mp4|rec12 audio-video (.mp4) past years]]
  
-**13.** //Friday 16 November 2018, 16-18// **[DB: 4.1-4.2,5.1-5.11]** [[http://apa.di.unipi.it/bsd/video/rec13_20181116.flv|Recording (current year)]]+A DW to support Analytical CRM AnalysisWrap up on DW design [[http://131.114.72.230/dsd/dsd.12.assignments.pdf|Exercises at home for the lesson 2023-14]].
  
-Recalls on: DBMS, from SQL to extended relational algebra. Exercises.\\ 
-**Software:** [[http://apa.di.unipi.it/bsd/JRS2019.zip|JRS (Java Relational System) DBMS]] (updated on 9 Jan 2019). 
  
-**14.** //Thursday 22 November 201816-18// **[DW: 5.1-5.4]** [[http://apa.di.unipi.it/bsd/video/rec14_20181122.flv|Recording (current year)]]+**2023-13.** //**Tuesday 7 November 202314-16, Room L1**//  **[DW: 2.3, 2.4]** [[http://131.114.72.230/dsd/video/dsd13a_20231107.mp4|rec13a audio-video (.mp4) current year]] and [[http://131.114.72.230/dsd/video/dsd13b_20211026.mp4|rec13b audio-video (.mp4past years]]
  
-OLAP systemsData Analysis Using SQLSimple reportsExamplesModerately Difficult ReportsExamples of variance reports. Solutions in SQL.+Multidimensional Cube model: OLAP OperationsThe extended cube and the lattice of cuboidsPivot tables in Excel.\\ 
 +**Additional learning material:** GHarveyExcel 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]].
  
-**15.** //Friday 23 November 201816-18// **[DW5.5-5.6]** [[http://apa.di.unipi.it/bsd/video/rec15_20181123.flv|Recording (current year)]]+**2023-14.** //Wednesday 8 November 202311-13//  **[DB4.1-4.2,5.1-5.11]** [[http://131.114.72.230/dsd/video/dsd14_20221102.mp4|rec14 audio-video (.mp4) current year]]
  
-Very Difficult Reports without Analytic SQL. Example of reports with ranksAnalytic Functions with the use of partitions and running totals. Examples. Analytic Functions with the use of moving windows. Examples.\\ +Recalls on: DBMS, from SQL to extended relational algebraExercises.  
-**Software:** [[https://docs.microsoft.com/en-us/sql/azure-data-studio/download +[[http://131.114.72.230/dsd/dsd.14.assignments.pdf|Exercises at home for the lesson 2023-15]].
-|Azure Data Studio]].+
  
 +**2023-15.** //Wednesday 15 November 2023, 11-36//   **[DW: 5.1-5.3]** [[http://131.114.72.230/dsd/video/dsd15_20211102.mp4|rec15 audio-video (.mp4) past years]]
  
-**16.** //Monday 26 November 2018, 14-16 **(Recover lesson - Room M1)**// **[DB: 6.1-6.6, 6.8, 7.1-7.2]** [[http://apa.di.unipi.it/bsd/video/rec16_20171117.flv|Recording (past years)]]+OLAP systemsData Analysis Using SQLSimple reportsExamplesModerately Difficult ReportsSolutions in SQL 
 +[[http://131.114.72.230/dsd/dsd.15.foodmart.pdf|Foodmart datawarehouse schema]].
  
-Recalls of relational DBMS internals: Storage, Indexing and Query EvaluationPhysical operators and physical plans for projectionselection, joins and grouping. Examples.\\ +**2023-16.** //Thursday 16 November 202314-16//  **[DW5.4-5.5]** [[http://131.114.72.230/dsd/video/dsd16_20211105.mp4|rec16 audio-video (.mp4past years]]
-**Software:** [[http://apa.di.unipi.it/bsd/JRS2019.zip|JRS (Java Relational SystemDBMS]] (updated on 9 Jan 2019).+
  
-**XX** <del>//Thursday 29 November 2018, 16-18//</del>+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://131.114.72.230/dsd/dsd.16.assignments.pdf|Exercises at home for the lesson 2023-17]].
  
-Lesson canceled due to institutional duties of the teacher.+**2023-17.** //**Tuesday 21 November 2023, 14-16, Room L1**//    **[DW: 5.5-5.6]** [[http://131.114.72.230/dsd/video/dsd17_20211109.mp4|rec17 audio-video (.mp4) past years]]
  
-**17.** //Friday 30 November 2018, 16-18// **[DW: 6.1-6.4]** [[http://apa.di.unipi.it/bsd/video/rec17_20181130.flv|Recording (current year)]]+Analytic Functions with the use of moving windowsExamples. Exercises on Analytic SQL. [[http://131.114.72.230/dsd/dsd.17.assignments.pdf|Exercises during the lesson and at home]] and [[http://131.114.72.230/dsd/dsd.17.solutions.txt|solutions]].
  
-Data Warehouse SystemsSpecial-Purpose Indexes and Star Query PlanBitmap indexesJoin indexesStar queries optimization and query plansExamplesTable partitioning.+**2023-18.** //Wednesday 22 November 2023, 11-13//   **[DB6.1-6.6, 6.8, 7.1-7.2]** [[http://131.114.72.230/dsd/video/dsd18_20211112.mp4|rec18 audio-video (.mp4) past years]]
  
-**18.** //Monday 3 December 201814-16 **(Recover lesson - Room M1)**// **[DW: 7.1-7.7]** [[http://apa.di.unipi.it/bsd/video/rec18_20181203.flv|Recording (current year)]]+Recalls of relational DBMS internals: Storage, Indexing and Query EvaluationPhysical operators and physical plans for projectionselection, joins and groupingExamples.
  
-The problem of materialized views selectionThe lattice of views and the greedy algorithm HRU for the selection of materialized viewsExamplesOther algorithms for the choice of the views to materialize with a workload and dimensional hierarchies.+**2023-19.** //Wednesday 29 November 2023, 11-13// **[DW: 6.1-6.4]** [[http://131.114.72.230/dsd/video/dsd19_20211116.mp4|rec19 audio-video (.mp4) past years]]
  
-**19.** //Wednesday 5 December 2018, 14-16 **(Recover lesson - Room Seminari Ovest, Dept. Computer Science**)// **[DW8.1-8.2, DB: 3.5.1-3.5.4]** [[http://apa.di.unipi.it/bsd/video/rec19_20171127.flv|Recording (past years)]]+Data Warehouse SystemsSpecial-Purpose Indexes and Star Query PlanBitmap indexesJoin indexesStar queries optimization and query plansExamplesTable partitioning.
  
-Recalls of functional dependency properties and how they are used to reason about the properties of the result of a queryProperties of the group-by operator.+**2023-19 bis.** //Thursday 30 November 2023, 14-16, **Room Seminari Est at the Computer Science Dept.**// **[DW: 6.5-6.8]**  [[http://131.114.72.230/dsd/video/dsd24_20211203.mp4|rec24 audio-video (.mp4) past years]]
  
-**XX** <del>//Thursday 6 December 201816-18//</del>+**For attending students:** Seminar (in Italian): //Sistema per l’analisi di dati statici di supporto alle decisioni// (V. Minei and R. Mosca[[https://www.sadasdb.com/en/|Sadas s.r.l.]])
  
-Lesson canceled due to institutional duties of the teacher.+**For non-attending students:** Data Warehousing trends: column-oriented DW, main-memory DW, Big Data framework. (see recorded lesson from past years).
  
-**20.** //Friday 7 December 2018, 11-13 **(Recover lesson - Room N1**)// **[DW: 8.3-8.6]** [[http://apa.di.unipi.it/bsd/video/rec20_20171201.flv|Recording (past years)]] 
  
-The problem of evaluating the group-by before the join operatorFirst caseInvariant groupingExamplesOther casesdouble grouping, grouping and countingExamples with star queries.+**2023-20.** //Wednesday 6 December 2023, 11-13// **[DW7.1-7.7]**[[http://131.114.72.230/dsd/video/dsd20_20211119.mp4|rec20 audio-video (.mp4) past years]]
  
-**21.** //Friday 7 December 2018, 14-16 **(Anticipated lesson - Room C1**)/// **[DW: 9.1-9.4]** [[http://apa.di.unipi.it/bsd/video/rec21_20171204.flv|Recording (past years)]]+The problem of materialized views selectionThe lattice of views and the greedy algorithm HRU for the selection of materialized viewsExamples. Other algorithms for the choice of the views to materialize with a workload and dimensional hierarchies [[http://131.114.72.230/dsd/dsd.20.assignments.pdf|Exercises at home for the lesson 2023-21]].
  
-The problem of query rewrite to use a materialized viewHypothesis and two approachesWith a compensation on the logical view planand with a transformation of logical query planExamples.+**2023-21.** //Thursday 7 December 2023, 14-16// **[DW8.1-8.2DB: 3.5.1-3.5.4]** [[http://131.114.72.230/dsd/video/dsd21_20221130.mp4|rec21 audio-video (.mp4) past years]]
  
-**22.** //Thursday 13 December 2018, 16-18// **[DW: 6.5-6.8]** [[http://apa.di.unipi.it/bsd/video/rec22_20181213.flv|Recording (current year)]]+Recalls of functional dependency properties and how they are used to reason about the properties of the result of a queryProperties of the group-by operator.
  
-Data Warehousing trends: column-oriented DWmain-memory DWBig Data framework.+**2023-22.** //**Monday 11 December 202314-16Room M1**// **[DW: 8.3-8.6]** [[http://131.114.72.230/dsd/video/dsd22_20221201.mp4|rec22 audio-video (.mp4) past years]]
  
-**23.** //Friday 14 December 201811-13 (**Recover lesson - Room N1**)//+The problem of evaluating the group-by before the join operatorFirst case: Invariant grouping. Examples. Other cases: double groupinggrouping and counting. Examples with star queries.
  
-Examples of written exams with solutionsQ. & A.\\ +**2023-23.** //Wednesday 13 December 2023, 11-13, ** Room M1**// **[DW9.1-9.4]** [[http://131.114.72.230/dsd/video/dsd23_20211130.mp4|rec23 audio-video (.mp4) past years]] 
-**Slides:** [[http://apa.di.unipi.it/bsd/exercises.pdf|exercises]].+ 
 +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.
  
-**24.** //Friday 14 December 2018, 16-18// 
  
-Examples of written exams with solutions. Q. & A. +=====Previous years=====
  
 +  * [[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)
  
mds/dsd/start.1558526242.txt.gz · Ultima modifica: 22/05/2019 alle 11:57 (5 anni fa) da Salvatore Ruggieri