Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Study Plan
The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
Modules | Credits | TAF | SSD |
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Compulsory activities for Embedded & Iot Systems
Compulsory activities for Smart Systems & Data Analytics
2° Year activated in the A.Y. 2023/2024
Modules | Credits | TAF | SSD |
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Compulsory activities for Embedded & Iot Systems
Compulsory activities for Robotics Systems
Compulsory activities for Smart Systems & Data Analytics
Modules | Credits | TAF | SSD |
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Compulsory activities for Embedded & Iot Systems
Compulsory activities for Smart Systems & Data Analytics
Modules | Credits | TAF | SSD |
---|
Compulsory activities for Embedded & Iot Systems
Compulsory activities for Robotics Systems
Compulsory activities for Smart Systems & Data Analytics
Modules | Credits | TAF | SSD |
---|
3 modules among the following
Legend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Advanced database & information systems (2022/2023)
Teaching code
4S009020
Teacher
Coordinator
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
Period
Semester 2 dal Mar 6, 2023 al Jun 16, 2023.
Learning objectives
The aim of the course is to allow students to acquire in-depth knowledge of the methodologies and tools necessary to manage large amounts of data in new database systems not based on the relational model (we will therefore consider systems based on semi-structured, object-oriented models, NoSQL and models with extensions for including time and space dimension). In particular, the systems that allow to store data produced by sensors and mobile devices will be analyzed so that a correct integration of these new data sources with the business information system is possible. At the end of the course, the student will be able to design and query non-traditional databases with tools of the NoSQL approach.
Prerequisites and basic notions
Basic knowledge of linear algebra, logic and programming. Knowledge of the relational model, SQL-2 query language.
Program
The course aims to provide the theoretical basis for the management of heterogeneous and distributed data:
• Fundamentals: data modeling, query languages, access structures (index)
• Distributed systems: distributed and parallel architectures for data management, transactions in distributed systems.
• New technologies for data management. NoSQL systems: semi-structured and document-based model, data design with complex structure, UML for the design of complex data, time and space dimension in complex data.
• Data integration: basic notions
Bibliography
Didactic methods
Teaching methods: lectures, classroom exercises with the teacher, teaching material (slides) and further exercises available on the eLearning platform, reception at the times indicated on the teacher's web page.
Learning assessment procedures
Written exam on the entire program and project on a specific NoSQL technology. The written test and the presentation of the project can take place on different days and also in different sessions and without any preferential order.
Evaluation criteria
To pass the exam, students will have to demonstrate that: - they have understood the concepts underlying the theory of relational databases and NoSQL of their design and implementation on real systems - be able to present their arguments in a precise and organic without digressions - knowing how to apply the knowledge acquired to solve application problems presented in the form of exercises, questions and projects.
Criteria for the composition of the final grade
The final grade is obtained from the arithmetic average between the project grade and the written grade.
Exam language
english