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mds:dsd:start [12/11/2021 alle 17:42 (19 mesi fa)] Salvatore Ruggieri [Class calendar] |
mds:dsd:start [11/01/2022 alle 07:59 (17 mesi fa)] Salvatore Ruggieri [Exams] |
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=====Mandatory teaching material ===== | =====Mandatory teaching material ===== | ||
- | * **[DW]** A. Albano, S. Ruggieri. [[http://patterns.di.unipi.it/bsd/ | + | * **[DW]** A. Albano, S. Ruggieri. [[http://fondamentidibasididati.it/wp-content/ |
- | * **[DB]** A. Albano. [[http:// | + | * **[DB]** A. Albano. [[http:// |
- | * Examples of [[http:// | + | * Examples of [[http:// |
=====Software===== | =====Software===== | ||
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^ Date ^ Hour ^ Room ^ Notes ^ | ^ Date ^ Hour ^ Room ^ Notes ^ | ||
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< | < | ||
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- | **2021-01.** //Tuesday 14 September 2021, 9-11// | + | **2021-01.** //Tuesday 14 September 2021, 9-11// |
Course overview. Need for Strategic Information. Information Systems in Organizations: | Course overview. Need for Strategic Information. Information Systems in Organizations: | ||
| | ||
- | **2021-02.** //Friday 17 September 2021, 16-18// | + | **2021-02.** //Friday 17 September 2021, 16-18// |
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. | ||
- | **2021-03.** //Tuesday 21 September 2021, 9-11// **[DB: 1.1, 2.1-2.5]** [[http:// | + | **2021-03.** //Tuesday 21 September 2021, 9-11// **[DB: 1.1, 2.1-2.5]** [[http:// |
- | Recalls: the Object Data Model. [[http:// | + | Recalls: the Object Data Model. [[http:// |
- | **2021-04.** //Friday 24 September 2021, 16-18// | + | **2021-04.** //Friday 24 September 2021, 16-18// |
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. | ||
- | [[http:// | + | [[http:// |
- | **2021-05.** //Tuesday 28 September 2021, 9-11// **[DW: 2.1, A.1]** | + | **2021-05.** //Tuesday 28 September 2021, 9-11// **[DW: 2.1, A.1]** |
- | The example of a data model for Master program exams. Presentation and discussion of the Hospital case study. | + | The example of a data model for Master program exams. Presentation and discussion of the Hospital case study. |
- | **2021-06.** //Friday 1 October 2021, 16-18// **[DB: 3.1-3.2]** | + | **2021-06.** //Friday 1 October 2021, 16-18// **[DB: 3.1-3.2]** |
Recalls: the relational model and relational algebra. Exercises. | Recalls: the relational model and relational algebra. Exercises. | ||
- | [[http:// | + | [[http:// |
- | **2021-07.** //Tuesday 5 October 2021, 9-11// **[DW: 2.1, 2.2, A.1, B.1]** [[http:// | + | **2021-07.** //Tuesday 5 October 2021, 9-11// **[DW: 2.1, 2.2, A.1, B.1]** [[http:// |
- | 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:// | + | 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:// |
- | **2021-08.** //Friday 8 October 2021, 16-18// **[DB: 3.2-3.4]** [[http:// | + | **2021-08.** //Friday 8 October 2021, 16-18// **[DB: 3.2-3.4]** [[http:// |
- | Recalls: the relational model and relational algebra. Logical trees. [[http:// | + | Recalls: the relational model and relational algebra. Logical trees. [[http:// |
- | **2021-09.** //Tuesday 12 October 2021, 9-11// | + | **2021-09.** //Tuesday 12 October 2021, 9-11// |
Discussion of students' | Discussion of students' | ||
- | **2021-10.** //Friday 15 October 2021, 16-18// **[DW: 3.1-3.5]** [[http:// | + | **2021-10.** //Friday 15 October 2021, 16-18// **[DW: 3.1-3.5]** [[http:// |
Data Warehouse design approaches. Data mart logical design. | Data Warehouse design approaches. Data mart logical design. | ||
- | **2021-11.** //Tuesday 19 October 2021, 9-11// **[DW: 3.1-3.5]**[[http:// | + | **2021-11.** //Tuesday 19 October 2021, 9-11// **[DW: 3.1-3.5]**[[http:// |
- | Slowly changing dimensions, fast changing dimensions, shared dimensions. Recursive hierarchies. Multivalued dimensions. [[http:// | + | Slowly changing dimensions, fast changing dimensions, shared dimensions. Recursive hierarchies. Multivalued dimensions. [[http:// |
- | **2021-12.** //Friday 22 October 2021, 16-18// **[DW: 4.1-4.8]** [[http:// | + | **2021-12.** //Friday 22 October 2021, 16-18// **[DW: 4.1-4.8]** [[http:// |
- | A DW to support Analytical CRM Analysis. Wrap up on DW design. | + | A DW to support Analytical CRM Analysis. Wrap up on DW design. |
- | **2021-13.** //Tuesday 26 October 2021, 9-11// **[DW: 2.3, 2.4]**[[http:// | + | **2021-13.** //Tuesday 26 October 2021, 9-11// **[DW: 2.3, 2.4]**[[http:// |
Multidimensional Cube model: OLAP Operations. The extended cube and the lattice of cuboids. Pivot tables in Excel. PowerPivot.\\ | Multidimensional Cube model: OLAP Operations. The extended cube and the lattice of cuboids. Pivot tables in Excel. PowerPivot.\\ | ||
**Additional learning material:** | **Additional learning material:** | ||
- | * G. Harvey. Excel 2013 All-in-One For Dummies, 2013. [[http:// | + | * G. Harvey. Excel 2013 All-in-One For Dummies, 2013. [[http:// |
* [[https:// | * [[https:// | ||
- | **2021-14.** //Friday 29 October 2021, 16-18// **[DB: 4.1-4.2, | + | **2021-14.** //Friday 29 October 2021, 16-18// **[DB: 4.1-4.2, |
Recalls on: DBMS, from SQL to extended relational algebra. Exercises. | Recalls on: DBMS, from SQL to extended relational algebra. Exercises. | ||
- | [[http:// | + | [[http:// |
- | **2021-15.** //Tuesday 2 November 2021, 9-11// | + | **2021-15.** //Tuesday 2 November 2021, 9-11// |
OLAP systems. Data Analysis Using SQL. Simple reports. Examples. Moderately Difficult Reports. Solutions in SQL. | OLAP systems. Data Analysis Using SQL. Simple reports. Examples. Moderately Difficult Reports. Solutions in SQL. | ||
- | [[http:// | + | [[http:// |
- | **2021-16.** //Friday 5 November 2021, 16-18// **[DW: 5.4-5.5]** [[http:// | + | **2021-16.** //Friday 5 November 2021, 16-18// **[DW: 5.4-5.5]** [[http:// |
- | 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. | + | 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. |
- | **2021-17.** //Tuesday 9 November 2021, 9-11// | + | **2021-17.** //Tuesday 9 November 2021, 9-11// |
- | Analytic Functions with the use of moving windows. Examples. Exercises on Analytic SQL. [[http:// | + | Analytic Functions with the use of moving windows. Examples. Exercises on Analytic SQL. [[http:// |
- | **2021-18.** //Friday 12 November 2021, 16-18// **[DB: 6.1-6.6, 6.8, 7.1-7.2]** [[http:// | + | **2021-18.** //Friday 12 November 2021, 16-18// **[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. | 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]** | + | **2021-19.** //Tuesday 16 November 2021, 9-11// **[DW: 6.1-6.4]** |
Data Warehouse Systems: Special-Purpose Indexes and Star Query Plan. Bitmap indexes. Join indexes. Star queries optimization and query plans. Examples. Table partitioning. | 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]** | + | **2021-20.** //Friday 19 November 2021, 16-18// **[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. | ||
+ | |||
+ | **2021-21.** //Tuesday 23 November 2021, 9-11// | ||
+ | |||
+ | 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]** [[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 | + | The problem of evaluating |
- | **2021-21.** // | + | **2021-23.** // |
- | ... | + | 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. | ||
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