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.

01. Introduction to the course: data and DBMS

02. Models and Languages ​​for Databases
  02.01 The relational model
  02.02 Database Management Systems (DMBS)
  02.03 SQL language
  02.04 Alternative approaches to the relational model, NoSQL and technologies for big data

03. Database Design 
  03.01 Conceptual design: the E/R model,
  03.02 Logical design
  03.03 Normalization techniques
  03.04 Physical desig

04. Introduction to data-mining
  04.01 General application scenarios (e.g. social media) of data-mining techniques
  04.02 Classification, clustering and prediction algorithms

05. Laboratory activities
  05.01 MySQL
  05.02 MongoDB
  05.03 Python
  05.04 Weka

It is suggested (not mandatory) to take the Database exam after courses on computer programming, computer architectures, algorithms and datasStructures.

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.

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

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.

Disability and Specific Learning Disorders (SLD)

Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.

To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.

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.

Disability and Specific Learning Disorders (SLD)

Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.

To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.