96793 - INFORMATION SYSTEMS AND DATABASE MANAGEMENT

Learning outcomes

Aim of the course is to understand the concepts and learn the techniques to access data stored in database systems for analytical purposes. In particular, the student will understand the main concepts of relational and noSQL database systems and will learn how to effectively extract data from those systems in order to prepare them for subsequent application of statistical and machine learning techniques. The course will deal with both the query languages of databases and the interfaces with programmatic languages, such as R or Python. At the end of the course the student is able: - to understand the structure of a given database, either relational or noSql; - to access the data stored in a Database Management System either with the specific standard languages or with programmatic interfaces.

Course contents

Understand data: elementary, complex and on the Web

Data modelling

Main concepts to describe and arrange data:

Relational database:

• Conceptual model (Entity-Relationship diagram)
• Logical model (relations schema)

noSQL database:

• document model
• key-value model

Database management

• Database management systems

The language to query databases:

• Query relational databases (SQL)
• Query noSQL databases

Data analysis

• Extract data, information
• Create data views 

Practice sessions with Python of Statistical Analysis on data from Databases and from the Web

Readings/Bibliography

Lectures will be based for relational databases on the book of Jeff Ullman and Jennifer Widom: "A First Course in Database Systems", for noSQL databases on Web documentation.

Further readings, examples and exercises will be made available weekly on “Virtual Learning Environment”.

Teaching methods

Lectures will be held in seminar and in computer rooms. Participation at the lecture (theory and practice) is a valid support for the comprehension of the covered topics.

Practice sessions are prevalent and fundamental to acquire the knowledge and competencies on the concepts and tools.

Assessment methods

Practical and written assessment (2 hours).The assessment consists in two parts.

In the first written part is required to design a data model based on given requisites (40%), and further to solve/answer to exercises and/or questions on course contents (20%). Use of teaching material is not allowed.

In the second practical part is required to write queries on a real database through SQL language (40%). It is allowed to use only the teaching material.

The final grade (over thirty) is computed applying percentages (weights) assigned to each type or request.

Teaching tools

Personal Computer and Open Source software to manage and query relational databases (MySQL) and Open Source software for data analysis (Python).

Office hours

See the website of Damiano Marino Somenzi