mds:dsd:start
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mds:dsd:start [12/12/2018 alle 19:55 (6 anni fa)] – [Class calendar] Salvatore Ruggieri | mds:dsd:start [17/10/2024 alle 19:18 (2 giorni fa)] (versione attuale) – Salvatore Ruggieri | ||
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- | < | + | ====== Decision Support Systems - Module I (6 ECTS): Decision Support Databases A.Y. 2024/25 ====== |
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- | ga(' | + | This is the first module of [[mds:dss:start|Decision Support Systems]] (801AA, 12 ECTS), previously called [[mds:dsd: |
- | ga(' | + | |
- | ga(' | + | 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 |
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- | ====== Decision Support Databases | + | |
- | 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, | ||
=====Instructor===== | =====Instructor===== | ||
- | * **Salvatore Ruggieri** | + | * **Salvatore Ruggieri** |
* Università di Pisa | * Università di Pisa | ||
* [[http:// | * [[http:// | ||
- | * [[ruggieri@di.unipi.it]] | + | * [[salvatore.ruggieri@unipi.it]] |
- | * **Office hours:** Tuesdays h 14:00 - 17:00 or by appointment, | + | * **Office hours:** Tuesdays h 14:00 - 16:00 or by appointment, |
- | =====Classes===== | ||
- | Lessons will be held at: Polo Didattico "L. Fibonacci", | + | =====Hours and rooms===== |
- | ^ Day of Week ^ Hour ^ Room ^ Type ^ | + | The following is the timetable |
- | | Thursday | 16:00 - 18:00 | Fib C1 | Lectures | + | |
- | | Friday| | + | |
+ | ^ Day of Week ^ Hour ^ Room ^ | ||
+ | | Tuesday | ||
+ | | Wednesday | ||
+ | | Thursday | ||
+ | | Friday | ||
- | =====Mandatory teaching material===== | ||
- | * **[DW]** | + | A [[https://teams.microsoft.com/l/team/19%3AqCllWc8f7UVglFSVL_MhR4ZjaLlWkUjUvJ3ROQdLSOA1%40thread.tacv2/ |
- | * **[DWSol]** | + | |
- | | + | |
- | * Examples | + | |
+ | =====Mandatory teaching material ===== | ||
- | =====Preliminary program | + | * **[DW]** A. Albano, S. Ruggieri. [[http:// |
+ | * **[DB]** A. Albano. [[http:// | ||
+ | * Examples of {{ : | ||
- | * [[https:// | + | =====Software===== |
- | * [[https:// | + | |
+ | * [[http:// | ||
+ | * [[https:// | ||
+ | * [[https:// | ||
- | =====Exams===== | + | =====Preliminary program and calendar===== |
- | __//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. | + | * [[https://esami.unipi.it/ |
- | Registration to exams is mandatory: | + | |
- | ^ Date ^ Hour ^ Room ^ | ||
- | | 23/ | ||
- | | 13/ | ||
- | =====Class calendar===== | ||
- | Recordings are password protected. Ask the teacher for credentials. | + | =====Exams===== |
- | + | ||
- | + | ||
- | **01.** //Monday 17 September 2018, 14-16// **[DW: 1.1-1.2]** [[http:// | + | |
- | + | ||
- | Course overview. Need for Strategic Information. Information Systems in Organizations: | + | |
- | + | ||
- | + | ||
- | **02.** //Wednesday 19 September 2018, 9-11// **[DW: 1.3-1.7]** [[http:// | + | |
- | + | ||
- | 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. | + | |
- | + | ||
- | **03.** //Thursday 27 September 2018, 16-18// **[DB: 1.1, 2.1-2.5]** [[http:// | + | |
- | + | ||
- | Recalls: the Object Data Model. | + | |
- | + | ||
- | **04.** //Friday 28 September 2018, 16-18// **[DW: 2.1]** [[http:// | + | |
- | + | ||
- | 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:// | + | |
- | + | ||
- | **05.** //Thursday 4 October 2018, 16-18// **[DW: 2.1, A.1]** [[http:// | + | |
- | + | ||
- | The example of a data model for Master program exams. Presentation and discussion of the Hospital case study. | + | |
- | + | ||
- | **06.** //Friday 5 October 2018, 16-18// **[DB: 3.1-3.2]** [[http:// | + | |
- | + | ||
- | Recalls: the relational model and relational algebra. Exercises. | + | |
- | + | ||
- | **07.** //Thursday 11 October 2018, 16-18// **[DW: 2.1, | + | |
- | + | ||
- | 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** < | + | |
- | + | ||
- | Lesson canceled to allow students' | + | |
- | + | ||
- | **08.** //Thursday 18 October 2018, 16-18// **[DB: 3.2-3.3]** [[http:// | + | |
- | + | ||
- | Recalls: the relational model and relational algebra. Logical trees. Exercises. | + | |
- | + | ||
- | **09.** //Friday 19 October 2018, 16-18// **[DW: 2.3,2.4]** [[http:// | + | |
- | + | ||
- | 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:// | + | |
- | * [[https:// | + | |
- | + | ||
- | **XX** < | + | |
- | + | ||
- | Lesson canceled due to institutional duties of the teacher. It will be recovered in November. | + | |
- | + | ||
- | **XX** < | + | |
- | + | ||
- | Lesson canceled due to institutional duties of the teacher. It will be recovered in November. | + | |
- | + | ||
- | **10.** //Thursday 8 November 2018, 16-18// **[DW: A.2, | + | |
- | + | ||
- | Discussion of students' | + | |
- | + | ||
- | **11.** //Friday 9 November 2018, 16-18// **[DW: 3.1-3.5]** [[http:// | + | |
- | + | ||
- | Data mart logical design. Slowly changing dimensions, fast changing dimensions, shared dimensions. Recursive hierarchies. Multivalued dimensions. Multivalued Dimensional Attributes. | + | |
- | + | ||
- | **12.** //Thursday 15 November 2018, 16-18// **[DB: 3.4], [DW: 4.1-4.8]** [[http:// | + | |
- | + | ||
- | Recalls on: ODM-to-Relational Mapping. A DW to support Analytical CRM Analysis. | + | |
- | + | ||
- | **13.** //Friday 16 November 2018, 16-18// **[DB: 4.1-4.2, | + | |
- | + | ||
- | Recalls on: DBMS, from SQL to extended relational algebra. Exercises.\\ | + | |
- | **Software: | + | |
- | + | ||
- | **14.** //Thursday 22 November 2018, 16-18// **[DW: 5.1-5.4]** [[http:// | + | |
- | + | ||
- | OLAP systems. Data Analysis Using SQL. Simple reports. Examples. Moderately Difficult Reports. Examples of variance reports. Solutions in SQL. | + | |
- | + | ||
- | **15.** //Friday 23 November 2018, 16-18// **[DW: 5.5-5.6]** [[http:// | + | |
- | + | ||
- | 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.\\ | + | |
- | **Software: | + | |
- | |Azure Data Studio]]. | + | |
- | + | ||
- | + | ||
- | **16.** //Monday 26 November 2018, 14-16 **(Recover lesson - Room M1)**// **[DB: 6.1-6.6, 6.8, 7.1-7.2]** [[http:// | + | |
- | + | ||
- | Recalls of relational DBMS internals: Storage, Indexing and Query Evaluation. Physical operators and physical plans for projection, selection, joins and grouping. Examples.\\ | + | |
- | **Software: | + | |
- | + | ||
- | **XX** < | + | |
- | + | ||
- | Lesson canceled due to institutional duties of the teacher. | + | |
- | + | ||
- | **17.** //Friday 30 November 2018, 16-18// **[DW: 6.1-6.4]** [[http:// | + | |
- | + | ||
- | Data Warehouse Systems: Special-Purpose Indexes and Star Query Plan. Bitmap indexes. Join indexes. Star queries optimization and query plans. Examples. Table partitioning. | + | |
- | + | ||
- | **18.** //Monday 3 December 2018, 14-16 **(Recover lesson - Room M1)**// **[DW: 7.1-7.7]** [[http:// | + | |
- | + | ||
- | 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. | + | |
- | + | ||
- | **19.** //Wednesday 5 December 2018, 14-16 **(Recover lesson - Room Seminari Ovest, Dept. Computer Science**)// | + | |
- | + | ||
- | 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. | + | |
- | **XX** <del>//Thursday 6 December 2018, 16-18//</ | + | __//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: |
- | Lesson canceled due to institutional duties of the teacher. | + | Registration |
- | **20.** //Friday 7 December 2018, 11-13 **(Recover lesson - Room N1**)// **[DW: 8.3-8.6]** [[http:// | + | **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 " |
- | 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. | + | ^ Date ^ Hour ^ Room ^ Notes ^ |
+ | | 6/ | ||
- | **21.** //Friday 7 December 2018, 14-16 **(Anticipated lesson - Room C1**)/// **[DW: 9.1-9.4]** [[http:// | + | =====Class calendar ===== |
- | 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 | + | Lessons will be **NOT** be live-streamed, but recordings |
- | **22.** //Thursday 13 December 2018, 16-18// **[DW: 6.5-6.8]** | + | To watch the recordings online, you must be connected to the [[https:// |
- | Data Warehousing trends: column-oriented DW, main-memory DW, Big Data framework. | + | 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. |
- | **23.** //Friday 14 December 2018, 11-13 (**Recover lesson - Room N1**)// | ||
- | Examples of written | + | ^ # ^ Date ^ Room ^ Topic ^ Mandatory teaching material ^ |
- | **Slides:** [[http://apa.di.unipi.it/bsd/exercises.pdf|exercises]]. | + | |01| 17/09 9-11 | Fib-C | Course overview. Need for Strategic Information. Information Systems in Organizations: |
+ | |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. | ||
+ | |03| 20/09 11-13 | Fib-L1 | Recalls: the Object Data Model. {{: | ||
+ | |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. {{: | ||
+ | |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. | ||
+ | |06| 27/09 11-13 | Fib-C1 | Recalls: the relational model and relational algebra. Exercises. {{: | ||
+ | |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. {{: | ||
+ | |08| 03/10 11-13 | Fib-A1 | Recalls: the relational model and relational algebra. Logical trees. {{: | ||
+ | |09| 04/10 11-13 | Fib-C1 | Discussion of students' | ||
+ | |10| 8/10 11-13 | Fib-C | Data Warehouse design approaches. Data mart logical design. | ||
+ | |11| 15/10 11-13 | Fib-C | Slowly changing dimensions, fast changing dimensions, shared dimensions. Recursive hierarchies. Multivalued dimensions. {{: | ||
+ | |12| 16/10 16-18 | Fib-H | A DW to support Analytical CRM Analysis. Wrap up on DW design. | ||
+ | |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:// | ||
+ | |14| 18/10 11-13 | Fib-C1 | Recalls on: DBMS, from SQL to extended relational algebra. Exercises. {{: | ||
+ | |15| 22/10 9-11 | Fib-C | OLAP systems. Data Analysis Using SQL. Simple reports. Examples. Moderately Difficult Reports. Solutions in SQL. {{: | ||
+ | |16| 25/10 11-13 | Fib-C1 | Examples of variance reports. Very Difficult Reports without Analytic SQL. Example of reports with ranks. Analytic Functions with the use of partitions and running totals. Examples. | ||
+ | |17| 31/10 11-13 | Fib-A1 | Analytic Functions with the use of moving windows. Examples. Exercises on Analytic SQL. {{: | ||
+ | |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:// | ||
+ | |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:// | ||
+ | |20| 08/11 11-13 | Fib-C1 | The problem of materialized views selection. The lattice of views and the greedy algorithm HRU for the selection of materialized views. Examples. Other algorithms for the choice of the views to materialize with a workload and dimensional hierarchies. | ||
+ | |21| 15/11 11-13 | Fib-C1 | Recalls of functional dependency properties and how they are used to reason about the properties of the result of a query. Properties of the group-by operator. | ||
+ | |22| 22/11 11-13 | Fib-C1 | The problem of evaluating the group-by before the join operator. First case: Invariant grouping. Examples. Other cases: double grouping, grouping and counting. Examples with star queries. | ||
+ | |23| 29/11 11-13 | Fib-C1 | The problem of query rewrite to use a materialized view. Hypothesis and two approaches: With a compensation on the logical view plan, and with a transformation of logical query plan. Examples. [[http:// | ||
+ | |24| 6/12 11-13 | Fib-C1 | Data Warehousing trends: column-oriented DW, main-memory DW, Big Data framework. [[http:// | ||
- | **24.** //Friday 14 December 2018, 16-18// | ||
- | Examples of written exams with solutions. Q. & A. | + | =====Previous years===== |
+ | * [[mds: | ||
+ | * [[mds: | ||
+ | * [[mds: | ||
+ | * [[mds: | ||
mds/dsd/start.1544644522.txt.gz · Ultima modifica: 12/12/2018 alle 19:55 (6 anni fa) da Salvatore Ruggieri