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mds:dsd:start [27/02/2019 alle 11:35 (5 anni fa)] Salvatore Ruggieri [Exams] |
mds:dsd:start [27/03/2024 alle 13:18 (5 settimane fa)] 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 ====== |
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The course 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. Particular 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. | 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). |
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| 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. |
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| <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===== |
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* **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. |
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=====Classes===== | |
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Lessons will be held at: Polo Didattico "L. Fibonacci", Via F. Buonarroti 4, Pisa.\\ | =====Hours and rooms===== |
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^ Day of Week ^ Hour ^ Room ^ Type ^ | ^ Day of Week ^ Hour ^ Room ^ |
| Thursday | 16:00 - 18:00 | Fib C1 | Lectures | | | Wednesday | 11:00 - 13:00 | Fib L1 | |
| Friday| 16:00 - 18:00 | Fib A1 | Lectures | | | Thursday | 14:00 - 16:00 | Fib L1 | |
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=====Mandatory teaching material===== | 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 ===== |
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* **[DW]** A. Albano, S. Ruggieri. [[http://apa.di.unipi.it/bsd/DWEssentialsWithoutSolutions.pdf|Decision Support Databases Essentials]], University of Pisa, 2017. | * **[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. |
* **[DWSol]** A. Albano, S. Ruggieri. Decision Support Databases Essentials: [[http://apa.di.unipi.it/bsd/DWEssentialsSolutions.pdf|Solutions to Case Studies]], University of Pisa, 2017. | * **[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). |
* **[DB]** A. Albano. [[http://apa.di.unipi.it/bsd/DBEssentials.pdf|Databases Essentials]], University of Pisa, 2016. | * Examples of {{ :mds:dsd:dsdsamples.pdf | written exams with solutions}} and [[http://131.114.72.230/dsd/dsd2020sample.pdf|written exam]]. |
* Examples of [[http://apa.di.unipi.it/bsd/BSDsamples.pdf|written exams with solutions]]. | =====Software===== |
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| * [[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 |
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=====Preliminary program and calendar===== | =====Preliminary program and calendar===== |
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* [[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]]. |
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=====Exams===== | =====Exams===== |
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__//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]] | |
| Registration to the written exam is mandatory (**pay attention at the deadline for registering!**): [[https://esami.unipi.it/esami2/|register here]]\\ |
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| **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.** |
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^ Date ^ Hour ^ Room ^ Notes ^ | ^ Date ^ Hour ^ Room ^ Notes ^ |
| 3/4/2019 | 9:00 - 11:00 | Fib-L1 | [[https://www.di.unipi.it/en/education/extra-sessions|Extra session]] | | | 28/5/2024 | 9:00 - 11:00 | TBD | | |
=====Class calendar===== | | 25/6/2024 | 9:00 - 11:00 | TBD | | |
| | 23/7/2024 | 9:00 - 11:00 | TBD | | |
| | 13/9/2024 | 11:00 - 13:00 | TBD | | |
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| <html> |
| <!-- [[https://didattica.di.unipi.it/en/appelli-straordinari/|Extra-ordinary exam]] --> |
| </html> |
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| =====Class calendar ===== |
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| Lessons will be **NOT** be live-streamed, but recordings of past years are available here for non-attending students.\\ |
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Recordings are password protected. Ask the teacher for credentials. | Some of recordings and teaching material are **password protected**. Ask the teacher for credentials.\\ |
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| 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]]. |
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**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)]] | **2023-01.** //Wednesday 20 September 2023, 11-13// **[DW: 1.1-1.2]** [[http://131.114.72.230/dsd/video/dsd01_20220915.mp4|rec01 audio-video (.mp4) past years]] |
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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. | 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. |
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**02.** //Wednesday 19 September 2018, 9-11// **[DW: 1.3-1.7]** [[http://apa.di.unipi.it/bsd/video/rec02_20180919.flv|Recording (current year)]] | **2023-02.** //Thursday 21 September 2023, 14-16// **[DW: 1.3-1.7]** [[http://131.114.72.230/dsd/video/dsd02_20180919.flv|rec02 audio-video (.flv) past years]] |
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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. | 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. |
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**03.** //Thursday 27 September 2018, 16-18// **[DB: 1.1, 2.1-2.5]** [[http://apa.di.unipi.it/bsd/video/rec03_20170925.flv|Recording (past years)]] | **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]] |
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Recalls: the Object Data Model. | Recalls: the Object Data Model. [[http://131.114.72.230/dsd/dsd.03.assignments.pdf|Exercises at home (Assignments I and II) for the lesson 2023-05]]. |
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**04.** //Friday 28 September 2018, 16-18// **[DW: 2.1]** [[http://apa.di.unipi.it/bsd/video/rec04_20170929.flv|Recording (past years)]] | **2023-04.** //Thursday 28 September 2023, 14-16// **[DW: 2.1]** [[http://131.114.72.230/dsd/video/dsd04_20170929.flv|rec04 audio-video (.flv) past years]] |
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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.\\ | 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. |
**Slides:** [[http://apa.di.unipi.it/bsd/UniversityCaseStudy.pdf|university requirements]]. | [[http://131.114.72.230/dsd/dsd.04.assignments.pdf|Exercises at home (University exams) for the lesson 2023-05]]. |
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**05.** //Thursday 4 October 2018, 16-18// **[DW: 2.1, A.1]** [[http://apa.di.unipi.it/bsd/video/rec05_20171002.flv|Recording (past years)]] | |
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The example of a data model for Master program exams. Presentation and discussion of the Hospital case study. | **2023-05.** //Wednesday 4 October 2023, 11-13// **[DW: 2.1, A.1]** [[http://131.114.72.230/dsd/video/dsd05_20210928.mp4|rec05 audio-video (.mp4) past years]] |
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**06.** //Friday 5 October 2018, 16-18// **[DB: 3.1-3.2]** [[http://apa.di.unipi.it/bsd/video/rec06_20181005.flv|Recording (current year)]] | 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]]. |
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Recalls: the relational model and relational algebra. Exercises. | **2023-06.** //Thursday 5 October 2023, 14-16// **[DB: 3.1-3.2]** [[http://131.114.72.230/dsd/video/dsd06_20211001.mp4|rec06 audio-video (.mp4) past years]] |
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**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)]] | 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]]. |
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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. | **2023-07.** //Wednesday 11 October 2023, 11-13//**[DW: 2.1, 2.2, A.1, B.1]** [[http://131.114.72.230/dsd/video/dsd07_20211005.mp4|rec07 audio-video (.mp4) past years]] |
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**XX** <del>//Friday 12 October 2018, 16-18//</del> | 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://131.114.72.230/dsd/dsd.07.assignments.pdf|Exercises at home (Travel agency) for the lesson 2023-09]]. |
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Lesson canceled to allow students' participation to the [[https://www.internetfestival.it/|Internet Festival]]. It will be recovered in November. | **2023-08.** //Thursday 12 October 2023, 14-16// **[DB: 3.2-3.4]** [[http://131.114.72.230/dsd/video/dsd08_20211008.mp4|rec08 audio-video (.mp4) past years]] |
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**08.** //Thursday 18 October 2018, 16-18// **[DB: 3.2-3.3]** [[http://apa.di.unipi.it/bsd/video/rec08_20171016.flv|Recording (past years)]] | Recalls: the relational model and relational algebra. Logical 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]]. |
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Recalls: the relational model and relational algebra. Logical trees. Exercises. | |
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**09.** //Friday 19 October 2018, 16-18// **[DW: 2.3,2.4]** [[http://apa.di.unipi.it/bsd/video/rec09_20181019.flv|Recording (current year)]] | **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]] |
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Multidimensional Cube model: OLAP Operations. The extended cube and the lattice of cuboids. Pivot tables in Excel. PowerPivot.\\ | Discussion of students' solutions of conceptual and logical design case studies. |
**Additional learning material:** | |
* G. Harvey. Excel 2013 All-in-One For Dummies, 2013. [[http://apa.di.unipi.it/bsd/PivotTable2013BookVIIchpt2.pdf|Chp. VII-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]]. | |
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**XX** <del>//Thursday 25 October 2018, 16-18//</del> | **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]] |
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Lesson canceled due to institutional duties of the teacher. It will be recovered in November. | Data Warehouse design approaches. Data mart logical design. |
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**XX** <del>//Friday 26 October 2018, 16-18//</del> | **2023-11.** //**Tuesday 24 October 2022, 14-16, Room L1**// **[DW: 3.1-3.5]** [[http://131.114.72.230/dsd/video/dsd11_20221020.mp4|rec11 audio-video (.mp4) past years]] |
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Lesson canceled due to institutional duties of the teacher. It will be recovered in November. | Slowly changing dimensions, fast changing dimensions, shared dimensions. Recursive hierarchies. Multivalued dimensions. [[http://131.114.72.230/dsd/dsd.11.assignments.pdf|Exercises at home (Travel agency extended) for the lesson 2023-12]]. |
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**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)]] | **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]] |
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Discussion of students' solutions of conceptual and logical design case studies: The airline companies. A Data Warehouse Design Methodology. Approaches. Design phases. Requirements specifications. | A DW to support Analytical CRM Analysis. Wrap up on DW design. [[http://131.114.72.230/dsd/dsd.12.assignments.pdf|Exercises at home for the lesson 2023-14]]. |
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**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)]] | |
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Data mart logical design. Slowly changing dimensions, fast changing dimensions, shared dimensions. Recursive hierarchies. Multivalued dimensions. Multivalued Dimensional Attributes. | **2023-13.** //**Tuesday 7 November 2023, 14-16, 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 (.mp4) past years]] |
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**12.** //Thursday 15 November 2018, 16-18// **[DB: 3.4], [DW: 4.1-4.8]** [[http://apa.di.unipi.it/bsd/video/rec12_20181115.flv|Recording (current year)]] | Multidimensional Cube model: OLAP Operations. The extended cube and the lattice of cuboids. Pivot tables in Excel.\\ |
| **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]]. |
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Recalls on: ODM-to-Relational Mapping. A DW to support Analytical CRM Analysis. | **2023-14.** //Wednesday 8 November 2023, 11-13// **[DB: 4.1-4.2,5.1-5.11]** [[http://131.114.72.230/dsd/video/dsd14_20221102.mp4|rec14 audio-video (.mp4) current year]] |
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**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)]] | Recalls on: DBMS, from SQL to extended relational algebra. Exercises. |
| [[http://131.114.72.230/dsd/dsd.14.assignments.pdf|Exercises at home for the lesson 2023-15]]. |
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Recalls on: DBMS, from SQL to extended relational algebra. Exercises.\\ | **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]] |
**Software:** [[http://apa.di.unipi.it/bsd/JRS2019.zip|JRS (Java Relational System) DBMS]] (updated on 9 Jan 2019). | |
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**14.** //Thursday 22 November 2018, 16-18// **[DW: 5.1-5.4]** [[http://apa.di.unipi.it/bsd/video/rec14_20181122.flv|Recording (current year)]] | OLAP systems. Data Analysis Using SQL. Simple reports. Examples. Moderately Difficult Reports. Solutions in SQL. |
| [[http://131.114.72.230/dsd/dsd.15.foodmart.pdf|Foodmart datawarehouse schema]]. |
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OLAP systems. Data Analysis Using SQL. Simple reports. Examples. Moderately Difficult Reports. Examples of variance reports. Solutions in SQL. | **2023-16.** //Thursday 16 November 2023, 14-16// **[DW: 5.4-5.5]** [[http://131.114.72.230/dsd/video/dsd16_20211105.mp4|rec16 audio-video (.mp4) past years]] |
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**15.** //Friday 23 November 2018, 16-18// **[DW: 5.5-5.6]** [[http://apa.di.unipi.it/bsd/video/rec15_20181123.flv|Recording (current year)]] | 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]]. |
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Very Difficult Reports without Analytic SQL. Example of reports with ranks. Analytic Functions with the use of partitions and running totals. Examples. Analytic Functions with the use of moving windows. Examples.\\ | **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]] |
**Software:** [[https://docs.microsoft.com/en-us/sql/azure-data-studio/download | |
|Azure Data Studio]]. | |
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| Analytic Functions with the use of moving windows. Examples. 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]]. |
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**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)]] | **2023-18.** //Wednesday 22 November 2023, 11-13// **[DB: 6.1-6.6, 6.8, 7.1-7.2]** [[http://131.114.72.230/dsd/video/dsd18_20211112.mp4|rec18 audio-video (.mp4) past years]] |
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Recalls of relational DBMS internals: Storage, Indexing and Query Evaluation. Physical operators and physical plans for projection, selection, joins and grouping. Examples.\\ | Recalls of relational DBMS internals: Storage, Indexing and Query Evaluation. Physical operators and physical plans for projection, selection, joins and grouping. Examples. |
**Software:** [[http://apa.di.unipi.it/bsd/JRS2019.zip|JRS (Java Relational System) DBMS]] (updated on 9 Jan 2019). | |
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**XX** <del>//Thursday 29 November 2018, 16-18//</del> | **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]] |
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Lesson canceled due to institutional duties of the teacher. | Data Warehouse Systems: Special-Purpose Indexes and Star Query Plan. Bitmap indexes. Join indexes. Star queries optimization and query plans. Examples. Table partitioning. |
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**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)]] | **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]] |
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Data Warehouse Systems: Special-Purpose Indexes and Star Query Plan. Bitmap indexes. Join indexes. Star queries optimization and query plans. Examples. Table partitioning. | **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.]]) |
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**18.** //Monday 3 December 2018, 14-16 **(Recover lesson - Room M1)**// **[DW: 7.1-7.7]** [[http://apa.di.unipi.it/bsd/video/rec18_20181203.flv|Recording (current year)]] | **For non-attending students:** Data Warehousing trends: column-oriented DW, main-memory DW, Big Data framework. (see recorded lesson from past years). |
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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. | |
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**19.** //Wednesday 5 December 2018, 14-16 **(Recover lesson - Room Seminari Ovest, Dept. Computer Science**)// **[DW: 8.1-8.2, DB: 3.5.1-3.5.4]** [[http://apa.di.unipi.it/bsd/video/rec19_20171127.flv|Recording (past years)]] | **2023-20.** //Wednesday 6 December 2023, 11-13// **[DW: 7.1-7.7]**[[http://131.114.72.230/dsd/video/dsd20_20211119.mp4|rec20 audio-video (.mp4) past years]] |
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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. | 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://131.114.72.230/dsd/dsd.20.assignments.pdf|Exercises at home for the lesson 2023-21]]. |
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**XX** <del>//Thursday 6 December 2018, 16-18//</del> | **2023-21.** //Thursday 7 December 2023, 14-16// **[DW: 8.1-8.2, DB: 3.5.1-3.5.4]** [[http://131.114.72.230/dsd/video/dsd21_20221130.mp4|rec21 audio-video (.mp4) past years]] |
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Lesson canceled due to institutional duties of the teacher. | 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. |
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**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)]] | **2023-22.** //**Monday 11 December 2023, 14-16, Room M1**// **[DW: 8.3-8.6]** [[http://131.114.72.230/dsd/video/dsd22_20221201.mp4|rec22 audio-video (.mp4) past years]] |
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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. | 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. |
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**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)]] | **2023-23.** //Wednesday 13 December 2023, 11-13, ** Room M1**// **[DW: 9.1-9.4]** [[http://131.114.72.230/dsd/video/dsd23_20211130.mp4|rec23 audio-video (.mp4) past years]] |
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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. | 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. |
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**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)]] | |
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Data Warehousing trends: column-oriented DW, main-memory DW, Big Data framework. | |
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**23.** //Friday 14 December 2018, 11-13 (**Recover lesson - Room N1**)// | |
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Examples of written exams with solutions. Q. & A.\\ | |
**Slides:** [[http://apa.di.unipi.it/bsd/exercises.pdf|exercises]]. | |
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**24.** //Friday 14 December 2018, 16-18// | |
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Examples of written exams with solutions. Q. & A. | =====Previous years===== |
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| * [[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) |
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