- Docente: Stefano Rizzi
- Credits: 6
- SSD: ING-INF/05
- Language: Italian
- Moduli: Stefano Rizzi (Modulo 1) Enrico Gallinucci (Modulo 2)
- Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
- Campus: Cesena
- Corso: Second cycle degree programme (LM) in Computer Science and Engineering (cod. 8614)
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from Sep 19, 2023 to Nov 29, 2023
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from Nov 07, 2023 to Dec 05, 2023
Learning outcomes
After the course, the student is skilled in business intelligence architectures and functionalities. In particular, the student is capable of designing and administrating enterprise data warehouses.
Course contents
Requirements
A prior knowledge and understanding of database systems, relational model, and SQL language is required to attend with profit this course. These notions are normally achieved by giving an exam of Databases or Information Systems.
Fluent spoken and written Italian is a necessary pre-requisite: all lectures and tutorials, and all study material will be in Italian.
Course Contents
- Business intelligence:
- the role of BI in the corporate information system;
- the BI pyramid.
- Data Warehousing:
- architectures;
- techniques for data analysis: reporting and OLAP;
- lifecycle:
- data source analysis;
- requirement analysis;
- conceptual design;
- workload and data volume;
- logical design;
- design of ETL procedures;
- physical design.
Readings/Bibliography
- Slides.
- M. Golfarelli, Stefano Rizzi. Data Warehouse: teoria e pratica della progettazione. McGraw-Hill, Second Edition, 2006.
- M. Berry, G. Linoff. Data mining techniques for marketing, sales, and customer support. John Wiley & Sons, 1997.
- B. Devlin. Data warehouse: from architecture to implementation. Addison-Wesley Longman, 1997.
- W.H. Inmon. Building the data warehouse. John Wiley & Sons, 1996.
- M. Jarke, M. Lenzerini, Y. Vassiliou, P. Vassiliadis. Fundamentals of data warehouse. Springer, 2000.
- R. Kimball, L. Reeves, M. Ross, W. Thornthwaite. The data warehouse lifecycle toolkit. John Wiley & Sons, 1998.
- I. Witten, E. Frank. Data mining. Morgan Kaufmann Publishers, 2000.
Teaching methods
- Lessons and exercises in the classroom
- Team exercises using virtual collaborative whiteboards
- Practice in the laboratory on widespread data warehousing tools
As concerns the teaching methods of this course unit, all students must attend Module 1, 2 on Health and Safety online
Assessment methods
Exams will be done either in presence or online, depending on the sanitary conditions and on the prescriptions given by the administration. In the online case, the Zoom and EOL platforms will be used. An exam consists of a 90-minutes written test, followed by a 30-minutes practical test; no books or notes can be accessed during both tests. The written test includes a design section, that requires to solve two exercises about conceptual and logical data warehouse design, and a theoretical section based on a few questions on all the course contents. The practical test uses the technological stack seen during lab lessons. Further details will be given during the lessons and in the "notes" field of AlmaEsami. The maximum evaluation score is 30/30.
To attend the exam, each student must sign up via AlmaEsami within a deadline. Those who cannot sign up must immediately communicate the problem to the teaching secretariat. Deciding whether to allow them to attend the exam or not is up to the teacher. Once the test results have been published, each student has one week to decide if (s)he wants to accept the grade or not. In case s(he) decides to refuse the grade, s(he) has to write an email to the teacher.
Teaching tools
Downloadable didactic material.
Teams platform for online teaching.
Miro platform for exercises.
Office hours
See the website of Stefano Rizzi
See the website of Enrico Gallinucci
SDGs
This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.