Strumenti Utente

Strumenti Sito


mds:dsd:start

Differenze

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

Link a questa pagina di confronto

Entrambe le parti precedenti la revisioneRevisione precedente
Prossima revisione
Revisione precedente
mds:dsd:start [21/11/2021 alle 12:48 (3 anni fa)] – [Class calendar] Salvatore Ruggierimds:dsd:start [20/09/2024 alle 19:36 (10 minuti fa)] (versione attuale) Salvatore Ruggieri
Linea 1: Linea 1:
-<html> +====== Decision Support Systems - Module I (6 ECTS): Decision Support Databases A.Y2024/25 ======
-<!-- Google Analytics --> +
-<script type="text/javascript" charset="utf-8"> +
-(function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function()+
-(i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o), +
-m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m) +
-})(window,document,'script','//www.google-analytics.com/analytics.js','ga');+
  
-ga('create', 'UA-34685760-1', 'auto', 'personalTracker', {'allowLinker'true}); +This is the first module of [[mds:dss:start|Decision Support Systems]] (801AA12 ECTS), previously called [[mds:dsd:2021|Decision Support Databases]] (662AA, 6 ECTS). 
-ga('personalTracker.require', 'linker'); +
-ga('personalTracker.linker:autoLink', ['pages.di.unipi.it', 'enforce.di.unipi.it', 'didawiki.di.unipi.it'); +
-   +
-ga('personalTracker.require''displayfeatures')+
-ga('personalTracker.send''pageview', 'ruggieri/teaching/dsd/'); +
-setTimeout("ga('send','event','adjusted bounce rate','30 seconds')",30000);  +
-</script> +
-<!-- End Google Analytics --> +
-<!-- Global site tag (gtag.js) - Google Analytics --> +
-<script async src="https://www.googletagmanager.com/gtag/js?id=G-LPWY0VLB5W"></script> +
-<script> +
-  window.dataLayer = window.dataLayer || []+
-  function gtag(){dataLayer.push(arguments);+
-  gtag('js', new Date());+
  
-  gtag('config''G-LPWY0VLB5W'); +The module 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 objectivesSpecific attention will be paid to themes such as conceptual and logical Data Warehouses designdata analysis using analytic SQLalgorithms for selecting materialized viewsdata warehouse systems technology (indexesstar query optimizationphysical designquery rewrite methods to use materialized views). A part of the course will be dedicated to collection of case studies.
-</script> +
-<!-- Capture clicks --> +
-<script> +
-jQuery(document).ready(function(){ +
-  jQuery('a[href$=".pdf"]').click(function() { +
-    var fname = this.href.split('/').pop(); +
-    ga('personalTracker.send''event' 'DSD''PDFs', fname); +
-  }); +
-  jQuery('a[href$=".r"]').click(function() { +
-    var fname = this.href.split('/').pop(); +
-    ga('personalTracker.send''event' 'DSD''Rs', fname)+
-  }); +
-  jQuery('a[href$=".zip"]').click(function() { +
-    var fname = this.href.split('/').pop(); +
-    ga('personalTracker.send', 'event',  'DSD', 'ZIPs', fname); +
-  }); +
-  jQuery('a[href$=".mp4"]').click(function() { +
-    var fname = this.href.split('/').pop(); +
-    ga('personalTracker.send', 'event',  'DSD', 'Videos', fname); +
-  }); +
-  jQuery('a[href$=".flv"]').click(function() { +
-    var fname = this.href.split('/').pop(); +
-    ga('personalTracker.send', 'event',  'DSD', 'Videos', fname); +
-  }); +
-}); +
-</script> +
-</html> +
-====== Decision Support Databases A.Y2021/22 ======+
  
-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. 
- 
-<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/]]
     * [[salvatore.ruggieri@unipi.it]]       * [[salvatore.ruggieri@unipi.it]]  
-    * <del>**Office hours:** Tuesdays h 14:00 - 17:00 or by appointment, Department of Computer Science, room 321/DO.</del> +    * **Office hours:** Tuesdays h 14:00 - 16:00 or by appointment, at the Department of Computer Science, room 321/DO, or via Teams.
-    * **Office hours only via Skype or Teams by appointmentSkype contact: salvatore.ruggieri**+
  
  
-=====Classes===== +=====Hours and rooms=====
- +
-Lessons will be also live-streamed on the [[https://teams.microsoft.com/l/team/19%3a3WUVDFKLmNbj2SXQnQzK1_BADY_6B1nZNbVXjg4qo8Y1%40thread.tacv2/conversations?groupId=a4c2f53f-0175-451f-96dc-f9f0bf8a1819&tenantId=c7456b31-a220-47f5-be52-473828670aa1|Teams space]].\\ +
  
 +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  ^  ^  Day of Week  ^  Hour  ^  Room  ^ 
-|  Tuesday  |  9:00 - 11:00  |  Fib M1  | +|  Tuesday  |  9:00 - 11:00  |  Fib  | 
-|  Friday   16:00 - 18:00  |  Fib  |+|  Wednesday   16:00 - 18:00  |  Fib H-Lab  | 
 +|  Thursday  |  11:00 - 13:00  |  Fib A1  | 
 +|  Friday  |  11:00 - 13:00  |  Fib L1  |
  
 +
 +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 ===== =====Mandatory teaching material =====
  
-  * **[DW]** A. Albano, S. Ruggieri. [[http://patterns.di.unipi.it/bsd/DWessential-2021.pdf|Decision Support Databases Essentials]], University of Pisa, 17 February 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/DBEssential-2021.pdf|DB Essentials]], University of Pisa, 1 December 2020. This is a self-contained excerpt (in English) from[[http://fondamentidibasididati.it|Fondamenti di basi di dati]] (in Italian, free download). +  * **[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/bsd/DSDsamples.pdf|written exams with solutions]] and [[http://patterns.di.unipi.it/bsd/dsd2020sample.pdf|written exam]].+  * Examples of {{ :mds:dsd:dsdsampleswithsolutions.pdf | written exams with solutions}} and {{ :mds:dsd:dsdsampleswithoutsolutions.pdf|written exams without solutions}}. 
 =====Software===== =====Software=====
  
-  * [[http://fondamentidibasididati.it/index.php/about-jrs/|JRS]] for practicing with logical and physical SQL query plans. JRS requires [[https://www.oracle.com/java/technologies/downloads/#java8|Java SE 8]] (need to register to download) +  * [[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]] client for connecting to SQL Server DBMS Foodmart database+  * [[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   * [[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/programma.php?c=52424&aa=2021|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-2021-2022/|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===== =====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. **The project of Module II can be discussed only after passing Module I and not later than one year since then.**
  
-Registration to exams 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  ^ ^  Date  ^  Hour  ^  Room  ^  Notes  ^
-|  19/11/2021   9:00 - 11:00  |  I-Lab | [[https://didattica.di.unipi.it/en/appelli-straordinari/|Extra-ordinary exam]] | +|  6/11/2024   9:00 - 11:00  |  TBD  | [[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>+
  
 =====Class calendar ===== =====Class calendar =====
  
-Lessons will be also live-streamed on the [[https://teams.microsoft.com/l/team/19%3a3WUVDFKLmNbj2SXQnQzK1_BADY_6B1nZNbVXjg4qo8Y1%40thread.tacv2/conversations?groupId=a4c2f53f-0175-451f-96dc-f9f0bf8a1819&tenantId=c7456b31-a220-47f5-be52-473828670aa1|Teams space]].\\ +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 protectedAsk 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]].
  
-To watch the recordings, please right click on the link and download the whole file. To watch the files locally to your computer, you can use e.g. [[http://www.videolan.org/vlc/|VLC media player]].+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.
  
  
-**2021-01.** //Tuesday 14 September 2021, 9-11//  **[DW: 1.1-1.2]** [[http://patterns.di.unipi.it/bsd/video/dsd01_20210914.mp4|rec01 audio-video (.mp4)]] +^ # ^ Date ^ Room ^ Topic ^ Mandatory teaching material ^  
- +|01| 17/09 9-11 | Fib-| 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)}} | 
-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 synthesisReports, Multidimensional data analysis, Exploratory data analysis. +|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)]] | **[DB1.1, 2.1-2.5]**  {{:mds:dsd:dsd03.pdf|slides03 (.pdf)}} | 
- +|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)}} | 
-**2021-02.** //Friday 17 September 2021, 16-18//  **[DW: 1.3-1.7]** [[http://patterns.di.unipi.it/bsd/video/dsd02_20180919.flv|rec02 audio-video (.flvpast years]] +|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)}} | 
- +|06| 27/09 11-13 | Fib-L1 | 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)}} | 
-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. +|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)}} | 
- +|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)}} | 
-**2021-03.** //Tuesday 21 September 2021, 9-11// **[DB: 1.1, 2.1-2.5]** [[http://patterns.di.unipi.it/bsd/video/dsd03_20210921.mp4|rec03 audio-video (.mp4)]] +|09| 04/10 11-13 | Fib-L1 | 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)}} | 
- +|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)}} | 
-Recalls: the Object Data Model. [[http://patterns.di.unipi.it/bsd/dsd.03.assignments.pdf|Exercises at home for the lesson 2021-05]]. +|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)}} | 
-**2021-04.** //Friday 24 September 2021, 16-18//  **[DW: 2.1]**  [[http://patterns.di.unipi.it/bsd/video/dsd04_20170929.flv|rec04 audio-video (.flvpast 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]]. | **[DW2.3, 2.4]**  {{:mds:dsd:dsd13.pdf|slides13 (.pdf)}} | 
- +|14| 18/10 11-13 | Fib-L1 | 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)]] | **[DB4.1-4.2,5.1-5.11]**  {{:mds:dsd:dsd14.pdf|slides14 (.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. +|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)}} | 
-[[http://patterns.di.unipi.it/bsd/dsd.04.assignments.pdf|Exercises at home for the lesson 2021-05]]. +|16| 25/10 11-13 | Fib-L1 | 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)}} | 
- +|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)}} | 
-**2021-05.** //Tuesday 28 September 2021, 9-11// **[DW: 2.1, A.1]**  [[http://patterns.di.unipi.it/bsd/video/dsd05_20210928.mp4|rec05 audio-video (.mp4)]] +|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)}} | 
- +|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)}} | 
-The example of a data model for Master program exams. Presentation and discussion of the Hospital case study.  [[http://patterns.di.unipi.it/bsd/dsd.05.assignments.pdf|Exercises at home for the lesson 2021-07]]. +|20| 08/11 11-13 | Fib-L1 | 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-L1 | 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)}} | 
- +|22| 22/11 11-13 | Fib-L1 | 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)}} | 
-**2021-06.** //Friday 1 October 2021, 16-18// **[DB: 3.1-3.2]**  [[http://patterns.di.unipi.it/bsd/video/dsd06_20211001.mp4|rec06 audio-video (.mp4)]] +|23| 29/11 11-13 | Fib-L1 | 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)}} | 
- +|24| 6/12 11-13 | Fib-L1 | 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)}} |
-Recalls: the relational model and relational algebra. Exercises.  +
-[[http://patterns.di.unipi.it/bsd/dsd.06.assignments.pdf|Exercises at home for the lesson 2021-08]]. +
- +
-**2021-07.** //Tuesday 5 October 2021, 9-11// **[DW: 2.1, 2.2, A.1, B.1]** [[http://patterns.di.unipi.it/bsd/video/dsd07_20211005.mp4|rec07 audio-video (.mp4)]] +
- +
-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/bsd/dsd.07.assignments.pdf|Exercises at home for the lesson 2021-09]]. +
- +
-**2021-08.** //Friday 8 October 2021, 16-18// **[DB: 3.2-3.4]** [[http://patterns.di.unipi.it/bsd/video/dsd08_20211008.mp4|rec08 audio-video (.mp4)]] +
- +
-Recalls: the relational model and relational algebra. Logical trees. [[http://patterns.di.unipi.it/bsd/dsd.08.exercises.pdf|Exercises with JRS]].  [[http://patterns.di.unipi.it/bsd/dsd.08.assignments.pdf|Exercises at home for the lesson 2021-09]]. +
- +
-**2021-09.** //Tuesday 12 October 2021, 9-11//  **[DW: A.2, B.2]** [[http://patterns.di.unipi.it/bsd/video/dsd09_20211012.mp4|rec09 audio-video (.mp4)]] +
- +
-Discussion of students' solutions of conceptual and logical design case studies.   +
- +
-**2021-10.** //Friday 15 October 2021, 16-18// **[DW: 3.1-3.5]** [[http://patterns.di.unipi.it/bsd/video/dsd10_20211015.mp4|rec10 audio-video (.mp4)]] +
- +
-Data Warehouse design approaches. Data mart logical design.  +
- +
-**2021-11.** //Tuesday 19 October 2021, 9-11// **[DW: 3.1-3.5]**[[http://patterns.di.unipi.it/bsd/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/bsd/dsd.11.assignments.pdf|Exercises at home for the lesson 2021-12]]. +
- +
-**2021-12.** //Friday 22 October 2021, 16-18// **[DW: 4.1-4.8]** [[http://patterns.di.unipi.it/bsd/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/bsd/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/bsd/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/bsd/PivotTable2013BookVIIchpt2.pdf|Chp. VII-2]] and [[http://patterns.di.unipi.it/bsd/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// **[DB4.1-4.2,5.1-5.11]** [[http://patterns.di.unipi.it/bsd/video/dsd14_20211029.mp4|rec14 audio-video (.mp4)]] +
- +
-Recalls on: DBMS, from SQL to extended relational algebra. Exercises.  +
-[[http://patterns.di.unipi.it/bsd/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/bsd/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/bsd/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/bsd/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/bsd/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/bsd/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/bsd/dsd.17.assignments.pdf|Exercises during the lesson and at home]] and [[http://patterns.di.unipi.it/bsd/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/bsd/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/bsd/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/bsd/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/bsd/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]**  +
- +
-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]**  +
- +
-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]**  +
- +
-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]**  +
- +
-Data Warehousing trends: column-oriented DW, main-memory DW, Big Data framework.+
  
  
 =====Previous years===== =====Previous years=====
  
-  * [[mds:dsd:2020|Decision Support Databases  A.Y. 2020/21]] +  * [[mds:dsd:2023|Decision Support Databases  A.Y. 2023/24]] 
-  * [[mds:dsd:2019|Decision Support Databases  A.Y. 2019/20]] +  * [[mds:dsd:2022|Decision Support Databases  A.Y. 2022/23]] 
-  * [[mds:dsd:2018|Decision Support Databases  A.Y. 2018/19]] +  * [[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.1637498926.txt.gz · Ultima modifica: 21/11/2021 alle 12:48 (3 anni fa) da Salvatore Ruggieri

Donate Powered by PHP Valid HTML5 Valid CSS Driven by DokuWiki