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Decision Support Databases A.Y. 2018/19

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.

Instructor

Classes

Lessons will be held at: Polo Didattico “L. Fibonacci”, Via F. Buonarroti 4, Pisa.

Day of Week Hour Room Type
Thursday 16:00 - 18:00 Fib C1 Lectures
Friday 16:00 - 18:00 Fib A1 Lectures

Mandatory teaching material

Preliminary program and calendar

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 Warehous 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. Registration to exams is mandatory: register here

Date Hour Room
23/1/2019 9:00 - 11:00 Fib-L1
13/2/2019 9:00 - 11:00 Fib-L1

Class calendar

Recordings are password protected. Ask the teacher for credentials.

01. Monday 17 September 2018, 14-16 [DW: 1.1-1.2] Recording (past years)

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.

02. Wednesday 19 September 2018, 9-11 [DW: 1.3-1.7] Recording (current year)

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] Recording (past years)

Recalls: the Object Data Model.

04. Friday 28 September 2018, 16-18 [DW: 2.1] Recording (past years)

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: university requirements.

05. Thursday 4 October 2018, 16-18 [DW: 2.1, A.1] Recording (past years)

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] Recording (current year)

Recalls: the relational model and relational algebra. Exercises.

07. Thursday 11 October 2018, 16-18 [DW: 2.1,2.2,A.1] Recording (current year)

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 Friday 12 October 2018, 16-18

Lesson canceled to allow students' participation to the Internet Festival. It will be recovered in November.

08. Thursday 18 October 2018, 16-18 [DB: 3.2-3.3] Recording (past years)

Recalls: the relational model and relational algebra. Logical trees. Exercises.

09. Friday 19 October 2018, 16-18 [DW: 2.3,2.4] Recording (current year)

Multidimensional Cube model: OLAP Operations. The extended cube and the lattice of cuboids. Pivot tables in Excel. PowerPivot.
Additional learning material:

XX Thursday 25 October 2018, 16-18

Lesson canceled due to institutional duties of the teacher. It will be recovered in November.

XX Friday 26 October 2018, 16-18

Lesson canceled due to institutional duties of the teacher. It will be recovered in November.

10. Thursday 8 November 2018, 16-18 [DW: A.2,3.1-3.5], [DWSol: B.2] Recording (past years)

Discussion of students' solutions of conceptual and logical design case studies: The airline companies. A Data Warehouse Design Methodology. Approaches. Design phases. Requirements specifications.

11. Friday 9 November 2018, 16-18 [DW: 3.1-3.5] Recording (past years)

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] Recording (current year)

Recalls on: ODM-to-Relational Mapping. A DW to support Analytical CRM Analysis.

13. Friday 16 November 2018, 16-18 [DB: 4.1-4.2,5.1-5.11] Recording (current year)

Recalls on: DBMS, from SQL to extended relational algebra. Exercises.
Software: JRS (Java Relational System) DBMS.

14. Thursday 22 November 2018, 16-18 [DW: 5.1-5.4]

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]

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.

16. Monday 26 November 2018, 14-16 (Recover lesson - Room M1) [DB: 6.1-6.6, 6.8, 7.1-7.2]

Recalls of relational DBMS internals: Storage, Indexing and Query Evaluation. Physical operators and physical plans for projection, selection, joins and grouping. Examples.

XX Thursday 29 November 2018, 16-18

Lesson canceled due to institutional duties of the teacher.

17. Friday 30 November 2018, 16-18 [DW: 6.1-6.8], [MPDB]

Data Warehouse Systems: Special-Purpose Indexes and Star Query Plan. Bitmap indexes. Join indexes. Star queries optimization and query plans. Examples of query plans for star queries. Column-Oriented Data Warehouse Systems.

18. Monday 3 December 2018, 14-16 (Recover lesson - Room M1) [DW: 7.1-7.7]

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) [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.

XX Thursday 6 December 2018, 16-18

Lesson canceled due to institutional duties of the teacher.

20. Friday 7 December 2018, 11-13 (Recover lesson - Room N1) [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.

21. Friday 7 December 2018, 16-18 [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.

22. Thursday 13 December 2018, 16-18

DW trends.

23. Friday 14 December 2018, 11-13 (Recover lesson - Room N1)

Examples of written exams with solutions. Q. & A.

24. Friday 14 December 2018, 16-18

Examples of written exams with solutions. Q. & A.

mds/dsd/start.txt · Ultima modifica: 17/11/2018 alle 16:40 (13 ore fa) da Salvatore Ruggieri