DATA BASES
BASI DI DATI
| A.Y. | Credits |
|---|---|
| 2023/2024 | 12 |
| Lecturer | Office hours for students | |
|---|---|---|
| Stefano Ferretti | Monday, 14:00-16:00 |
| Teaching in foreign languages |
|---|
|
Course with optional materials in a foreign language
English
This course is entirely taught in Italian. Study materials can be provided in the foreign language and the final exam can be taken in the foreign language. |
Assigned to the Degree Course
| Date | Time | Classroom / Location |
|---|
| Date | Time | Classroom / Location |
|---|
Learning Objectives
The aim of this course is to introduce information systems, describe data models and conceptual, logical and physical design techniques for the development and management of databases. Secondly, it introduces the main methodologies for data mining.
Program
-- First semester --
01. Introduction to the course: data and DBMS
01.01 Introduction to data management, data analysis, big data
01.02 Database definition
01.03 Introduction to the Data Base Management Systems (DBMS)
02. Models and Languages for Databases
02.01 Relational model
02.02 Database Management Systems (DMBS)
02.03 Integrity constraints, primary keys
03. SQL
03.01 DDL (Data Definition Language)
03.02 DML (Data Manipulation Language)
03.03 Nested queries
03.04 Operators, views, procedures, trigger
04. MySQL
04.01 Introduction
04.02 Lab
05. DB Design - Conceptual design
05.01 E/R model
05.02 Analysis
05.03 Design strategies
05.04 Quality verification
-- Second semester --
06. Logical design
06.01 E/R restructuring
06.02 Translation of the relational model
06.03 Quality assessment
07. Normalization
07.01 Data redundancies
07.02 Normal forms: Boyce-Codd, 3rd normal form
07.03 Decomposition algorithm
08. Physical design
08.01 Memory organization
08.02 Techniques for data management
08.03 Indexed Sequential Access Method (ISAM)
08.04 B-tree, B+ Tree
09. NoSQL
09.01 Intro to NoSQL DBMS
09.02 MongoDb
10. Python
10.01 Introduction to the language
10.02 Python and DBs
10.03 PYthon for data analysis
11. Data Analytics
11.01 Data mining
11.02 Data preparation
11.03 Clustering
11.04 Classification
11.05 Prediction
12. Applications and tools for data analysis
12.01 Weka
12.02 Python
12.03 Use cases
Bridging Courses
It is suggested (not mandatory) to take the Database exam after courses on computer programming, computer architectures, algorithms and data structures, operating systems.
Learning Achievements (Dublin Descriptors)
Knowledge and understanding: the student will acquire the main knowledge related to database design methodologies, SQL query language, architecture of database management systems; he will be able to understand the structure of information systems designed according to the relational model. In addition, the student will acquire the main knowledge related to the extraction of information from data analysis.
Ability to apply knowledge and understanding: the student will be able to apply the acquired knowledge to design relational databases and implement them using systems such as MySQL. It will also be able to develop a project for the construction of an IT system. Finally, he will be able to understand and (partially) apply data mining techniques for extracting information from a set of raw data.
Autonomy of judgment: the student will be able to evaluate the correctness and efficiency of a database designed according to the relational model.
Teaching Material
The teaching material prepared by the lecturer in addition to recommended textbooks (such as for instance slides, lecture notes, exercises, bibliography) and communications from the lecturer specific to the course can be found inside the Moodle platform › blended.uniurb.it
Teaching, Attendance, Course Books and Assessment
- Teaching
Frontal lessons and laboratory activities
- Attendance
Not mandatory
- Course books
Paolo Atzeni, Stefano Ceri, Stefano Paraboschi, Riccardo Torlone, Basi di dati - 5/ed, 2018, ISBN: 9788838694455
- Assessment
Project (possibly in group, max 3 people), to be decided with the teacher
Written exam
Oral exam: mandatory for the project discussion, optional on the program course.
- Disabilità e DSA
Le studentesse e gli studenti che hanno registrato la certificazione di disabilità o la certificazione di DSA presso l'Ufficio Inclusione e diritto allo studio, possono chiedere di utilizzare le mappe concettuali (per parole chiave) durante la prova di esame.
A tal fine, è necessario inviare le mappe, due settimane prima dell’appello di esame, alla o al docente del corso, che ne verificherà la coerenza con le indicazioni delle linee guida di ateneo e potrà chiederne la modifica.
Additional Information for Non-Attending Students
- Teaching
Material coming from frontal lessons and laboratory activities
- Attendance
Not mandatory
- Course books
Paolo Atzeni, Stefano Ceri, Stefano Paraboschi, Riccardo Torlone, Basi di dati - 5/ed, 2018, ISBN: 9788838694455
- Assessment
Individual project (to be decided with the teacher)
Written exam
Oral exam: mandatory for the project discussion, optional on the program course.
- Disabilità e DSA
Le studentesse e gli studenti che hanno registrato la certificazione di disabilità o la certificazione di DSA presso l'Ufficio Inclusione e diritto allo studio, possono chiedere di utilizzare le mappe concettuali (per parole chiave) durante la prova di esame.
A tal fine, è necessario inviare le mappe, due settimane prima dell’appello di esame, alla o al docente del corso, che ne verificherà la coerenza con le indicazioni delle linee guida di ateneo e potrà chiederne la modifica.
| « back | Last update: 10/07/2023 |
