Teaching code

4S00037

Credits

12

Coordinator

Alberto Belussi

Language

Italian

Also offered in courses:

• Databases and WEB of the course Bachelor's degree in Bioinformatics

Scientific Disciplinary Sector (SSD)

ING-INF/05 - INFORMATION PROCESSING SYSTEMS

Moodle Seminars 0

The teaching is organized as follows:

Learning objectives

The course aims to provide the necessary skills for: (i) the design of data according to the requirements with reference to different application contexts and within the production process of software systems; (ii) effective and efficient management and use of data; (iii) the use of a system for the management of relational databases in order to create, manage and query databases; (iv) the development of applications that interact with relational databases. At the end of the course the student must demonstrate knowledge and understanding of data models and query languages that characterize systems for data management and knowledge of the fundamental mechanisms to develop applications that interact with a database; have the ability to apply the acquired knowledge and understanding skills for the design of a data collection in an effective way compared to a set of application requirements, the ability to query and efficiently use the data managed by a system, the ability to design and implement an application that interacts with a data- base; know how to develop the skills necessary to continue the studies independently in the field of data management systems and software solutions development.

Prerequisites and basic notions

Basic knowledge of linear algebra, logic, programming and operating systems (secondary memory and file system)

Program

The program is specified for each module as follows.
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Module of Theory
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- 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.
- 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.
- Interacting with a database system: languages for the definition, querying and update of a database. The relational algebra. Optimization of algebraic expressions. SQL: select-from-where statement.
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Module of Lab
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- Introduction to the relational database management system (RDBMS) PostgreSQL.
- Introduction to the use of SQL in PostgreSQL.
- Query Optimization.
- Introduction to the transaction.
- Introduction to Python Language.
- Database access from applications written in Java/Python.
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Module of Database technology
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- The internal architecture of a DBMS. Transactions. Transactions properties. The concurrency control: schedules, the two-phase locking. Access methods (indexes): primary and secondary indexes, B-+tree, hashing based access methods. Query execution and optimization.
- Techniques for the interaction between a DBMS and an application: JDBC and ORM.
- Semi-structured data: XML and JSON, MongoDB (hints).

Bibliography

Didactic methods

Theory Module
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Teaching delivery methods: face-to-face lectures (also available in recorded streaming; recordings will be made available on request for students unable to attend in person or in streaming), 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.
Laboratory Module
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Teaching delivery methods: classroom lectures and exercises in the computer lab , didactic material (slides) and further exercises on the eLearning platform, individual reception at the times agreed with the teacher.
Database Technologies Module
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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 page web site of the teacher.

Learning assessment procedures

The exam is composed of three parts: theory, technologies and lab.
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Module of Theory
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For the modules of "Teoria" and "Tecnologie per le basi di dati" the exam consists of a written test with a duration of 2.5 hours containing: (i) an exercise about the conceptual modeling (using the E-R model) and the logical modeling (using the relational model) of a database; (ii) some exercises about the specification of queries in relational algebra on a given database; (iii) some exercises on semi-structured data and some questions on the theory.
On the e-learning platform in the section "TEMI D'ESAME E ALTRI ESERCIZI RIEPILOGATIVI" some tests of the previous years are published.
During the year, it is also possible to undergo the mid-term tests: these tests are fixed by the teacher in agreement with the students and are managed on the eLearning platform. These are two tests: the first test regards the design of a relational database: conceptual design (E-R model) and logic design (relational model), and the specification of queries on a relational database in relational algebra, this test weighs 1/2 of the final grade; the second test regards the program of the module Databases Technologies, and it weighs 1/4 of the final grade.
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Module of Lab
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For the "Laboratory" module there is a one-hour written test which includes questions and exercises on SQL queries and on writing code in Java or Python for accessing a relational database.
The laboratory test weighs 1/4 of the overall grade.

Evaluation criteria

To pass the exam, the students must show that:
- they have understood the concepts related to the theory of relational databases and their design and implementation on database management systems
- they are able to describe the concepts in a clear and exhaustive way without digressions
- they are able to apply the acquired knowledge to solve application scenarios described by means of exercises, questions and projects.

Criteria for the composition of the final grade

The total grade (theory+laboratory) is given by the following average: theory_grade*3/4 + lab_grade*1/4.

Exam language

italiano