mds:dsd:2023
Differenze
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| mds:dsd:2023 [26/08/2026 alle 12:36 (5 giorni fa)] – [Previous years] Salvatore Ruggieri | mds:dsd:2023 [26/08/2026 alle 12:38 (5 giorni fa)] (versione attuale) – eliminata Salvatore Ruggieri | ||
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| - | ====== Decision Support Systems - Module I (6 ECTS): Decision Support Databases A.Y. 2023/24 ====== | ||
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| - | This is the first module of [[mds: | ||
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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, | ||
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| - | =====Instructor===== | ||
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| - | * **Salvatore Ruggieri** | ||
| - | * Università di Pisa | ||
| - | * [[http:// | ||
| - | * [[salvatore.ruggieri@unipi.it]] | ||
| - | * **Office hours:** Tuesdays h 14:00 - 16:00 or by appointment, | ||
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| - | =====Hours and rooms===== | ||
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| - | ^ Day of Week ^ Hour ^ Room ^ | ||
| - | | Wednesday | ||
| - | | Thursday | ||
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| - | A [[https:// | ||
| - | =====Mandatory teaching material ===== | ||
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| - | * **[DW]** A. Albano, S. Ruggieri. [[http:// | ||
| - | * **[DB]** A. Albano. [[http:// | ||
| - | * Examples of {{ : | ||
| - | =====Software===== | ||
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| - | * [[http:// | ||
| - | * [[https:// | ||
| - | * [[https:// | ||
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| - | =====Preliminary program and calendar===== | ||
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| - | * [[https:// | ||
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| - | =====Exams===== | ||
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| - | __//There are no mid-terms// | ||
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| - | Registration to the written exam is mandatory (**pay attention at the deadline for registering!**): | ||
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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 " | ||
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| - | ^ Date ^ Hour ^ Room ^ Notes ^ | ||
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| - | =====Class calendar ===== | ||
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| - | Lessons will be **NOT** be live-streamed, | ||
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| - | 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:// | ||
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| - | **2023-01.** //Wednesday 20 September 2023, 11-13// **[DW: 1.1-1.2]** [[http:// | ||
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| - | Course overview. Need for Strategic Information. Information Systems in Organizations: | ||
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| - | **2023-02.** //Thursday 21 September 2023, 14-16// **[DW: 1.3-1.7]** | ||
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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. | ||
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| - | **2023-03.** //Wednesday 27 September 2023, 11-13// **[DB: 1.1, 2.1-2.5]** [[http:// | ||
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| - | Recalls: the Object Data Model. [[http:// | ||
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| - | **2023-04.** //Thursday 28 September 2023, 14-16// **[DW: 2.1]** | ||
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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. | ||
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| - | **2023-05.** //Wednesday 4 October 2023, 11-13// **[DW: 2.1, A.1]** | ||
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| - | The example of a data model for Master program exams. Presentation and discussion of the Hospital case study. | ||
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| - | **2023-06.** //Thursday 5 October 2023, 14-16// **[DB: 3.1-3.2]** | ||
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| - | Recalls: the relational model and relational algebra. Exercises. | ||
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| - | **2023-07.** //Wednesday 11 October 2023, 11-13// | ||
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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. [[http:// | ||
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| - | **2023-08.** //Thursday 12 October 2023, 14-16// **[DB: 3.2-3.4]** [[http:// | ||
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| - | Recalls: the relational model and relational algebra. Logical trees. [[http:// | ||
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| - | **2023-09.** //Wednesday 18 October 2023, 11-13// **[DW: A.2, B.2]** [[http:// | ||
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| - | Discussion of students' | ||
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| - | **2023-10.** //Thursday 19 October 2023, 14-16// **[DW: 3.1-3.5]** [[http:// | ||
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| - | Data Warehouse design approaches. Data mart logical design. | ||
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| - | **2023-11.** //**Tuesday 24 October 2022, 14-16, Room L1**// **[DW: 3.1-3.5]** [[http:// | ||
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| - | Slowly changing dimensions, fast changing dimensions, shared dimensions. Recursive hierarchies. Multivalued dimensions. [[http:// | ||
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| - | **2023-12.** //Thursday 2 November 2023, 14-16// | ||
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| - | A DW to support Analytical CRM Analysis. Wrap up on DW design. | ||
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| - | **2023-13.** //**Tuesday 7 November 2023, 14-16, Room L1**// | ||
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| - | 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:// | ||
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| - | **2023-14.** //Wednesday 8 November 2023, 11-13// | ||
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| - | Recalls on: DBMS, from SQL to extended relational algebra. Exercises. | ||
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| - | **2023-15.** //Wednesday 15 November 2023, 11-36// | ||
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| - | OLAP systems. Data Analysis Using SQL. Simple reports. Examples. Moderately Difficult Reports. Solutions in SQL. | ||
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| - | **2023-16.** //Thursday 16 November 2023, 14-16// | ||
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| - | 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. | ||
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| - | **2023-17.** //**Tuesday 21 November 2023, 14-16, Room L1**// | ||
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| - | Analytic Functions with the use of moving windows. Examples. Exercises on Analytic SQL. [[http:// | ||
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| - | **2023-18.** //Wednesday 22 November 2023, 11-13// | ||
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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. | ||
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| - | **2023-19.** //Wednesday 29 November 2023, 11-13// **[DW: 6.1-6.4]** [[http:// | ||
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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. | ||
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| - | **2023-19 bis.** //Thursday 30 November 2023, 14-16, **Room Seminari Est at the Computer Science Dept.**// **[DW: 6.5-6.8]** | ||
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| - | **For attending students:** Seminar (in Italian): //Sistema per l’analisi di dati statici di supporto alle decisioni// (V. Minei and R. Mosca, [[https:// | ||
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| - | **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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| - | **2023-20.** //Wednesday 6 December 2023, 11-13// **[DW: 7.1-7.7]**[[http:// | ||
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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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| - | **2023-21.** //Thursday 7 December 2023, 14-16// **[DW: 8.1-8.2, DB: 3.5.1-3.5.4]** [[http:// | ||
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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. | ||
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| - | **2023-22.** //**Monday 11 December 2023, 14-16, Room M1**// **[DW: 8.3-8.6]** [[http:// | ||
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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. | ||
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| - | **2023-23.** //Wednesday 13 December 2023, 11-13, ** Room M1**// **[DW: 9.1-9.4]** [[http:// | ||
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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. | ||
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