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
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Compulsory activities for Embedded & Iot SystemsCompulsory activities for Smart Systems & Data Analytics2° Year activated in the A.Y. 2022/2023
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Compulsory activities for Embedded & Iot SystemsCompulsory activities for Robotics SystemsCompulsory activities for Smart Systems & Data Analytics| Modules | Credits | TAF | SSD |
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Compulsory activities for Embedded & Iot SystemsCompulsory activities for Smart Systems & Data Analytics| Modules | Credits | TAF | SSD |
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Compulsory activities for Embedded & Iot SystemsCompulsory activities for Robotics SystemsCompulsory activities for Smart Systems & Data Analytics| Modules | Credits | TAF | SSD |
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3 modules among the followingLegend | 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.
Data warehouse and integration (2022/2023)
Teaching code
4S009009
Teacher
Coordinator
Credits
6
Also offered in courses:
- Programming and database of the course Master's degree in Data Science
Language
English
Scientific Disciplinary Sector (SSD)
ING-INF/05 - INFORMATION PROCESSING SYSTEMS
Period
Semester 2 dal Mar 6, 2023 al Jun 16, 2023.
Learning objectives
The goal of the course is to enable students to master the engineering methods and processes that are necessary to manage modern information system, and especially data-intensive systems, to operate on large data collections and to understand the utility and methods of business analysis, obtaining useful knowledge to improve the decision-making process. As a consequence, the course will expose the students to some of the most advanced methodologies adopted to understand the conceptual and technological problems encountered in the design and implementation of solutions based on analyses for complex systems starting from collections of data that must be integrated, organized and analyzed mainly through automatic tools.
Prerequisites and basic notions
Theory or relational databases
Program
1. Introduction to database management systems (DBMS): architectures and functionalities of a DBMS. Physical and logical data independence. Data models. Concepts of model, schema and instance of a database. Languages for database systems. DBMS vs. file system. Information Systems and Data Science.
2. The relational theory: basic concepts.
3. Interacting with a database system: languages for the definition, querying and update of a database. SQL: select-from-where statement, join in SQL, the GROUP BY and ORDER BY clauses, using subqueries. Views.
4. Conceptual database design: conceptual data models. The Entity-Relationship model (ER). Elements of the ER model: entities, attributes, relationships, ISA hierarchies and cardinality constraints. Logical database design: logical data models, the relational data model. Elements of the relational data models: relations and integrity constraints. Mapping between conceptual schemas in ER model and logical schema in the relational model.
5. Decision support systems.
1. Datawarehouse systems
2. Designing Data Warehouse on integrated data (GAV and LAV approaches)
3. OLAP queries
Bibliography
Didactic methods
In-person classes and practical sessions
Learning assessment procedures
The exam consists of a written test (2 hours), possibly supplemented by an oral, containing some open questions about theory concepts, an exercise about the conceptual modeling and the logical modeling of a datawarehouse, and some exercises about the specification of queries in SQL on the designed datawarehouse.
Evaluation criteria
To pass the exam, the students must show that:
- they have understood the concepts related to the theory of relational databases and data warehouses and their design;
- they are able to describe the concepts in a clear and exhaustive way;
- they are able to apply the acquired knowledge to solve application scenarios described by means of questions and exercises.
The written exam will be evaluated with at most 33 points (30 cum Laude).
Criteria for the composition of the final grade
The final mark will be the mark obtained in the written exam, possibly supplemented by the mark obtained during the oral test.
Exam language
Inglese
