Servizi per la didattica
PORTALE DELLA DIDATTICA

Data Science and Database Technology

01SQJOV

A.A. 2018/19

Course Language

English

Course degree

Master of science-level of the Bologna process in Computer Engineering - Torino

Course structure
Teaching Hours
Lezioni 46
Esercitazioni in aula 22
Esercitazioni in laboratorio 12
Tutoraggio 60
Teachers
Teacher Status SSD h.Les h.Ex h.Lab h.Tut Years teaching
Chiusano Silvia Anna Professore Associato ING-INF/05 46 1 12 0 2
Teaching assistant
Espandi

Context
SSD CFU Activities Area context
ING-INF/05
ING-INF/05
4
4
F - Altre (art. 10, comma 1, lettera f)
B - Caratterizzanti
Abilità informatiche e telematiche
Ingegneria informatica
2018/19
The course is taught in English. The course, compulsory for the Master degree in Computer Engineering, is offered on the 1st semester of the 1st year. The course addresses the fundamental issues in the technology of database management systems and introduces database management techniques for data warehouses (database systems specialized in strategic decision support), typically characterized by the need of managing very large databases. Both traditional OLAP (On Line Analytical Processing) analysis techniques and complex data mining techniques will be addressed. Laboratory sessions allow experimental activities, both on technological characteristics and data analysis, on the most widespread commercial and open-source products.
The course is taught in English. The course, compulsory for the Master degree in Computer Engineering, is offered on the 1st semester of the 1st year. The course addresses the fundamental issues in the technology of database management systems and introduces database management techniques for data warehouses (database systems specialized in strategic decision support), typically characterized by the need of managing very large databases. Both traditional OLAP (On Line Analytical Processing) analysis techniques and complex data mining techniques will be addressed. Laboratory sessions allow experimental activities, both on technological characteristics and data analysis, on the most widespread commercial and open-source products.
- Knowledge of the main technological characteristics of a database management system: concurrent data access management, reliability, physical level structures, data access optimization. - Ability to design the physical data structures for a relational database. - Knowledge of distributed database system architecture and replication management. - Knowledge of active database systems and SQL statements for trigger definition. - Ability to write triggers in the SQL language. - Knowledge of data warehouse architecture and of the methodology for conceptual, logical, and physical design of a data warehouse. - Ability to design a data warehouse. - Knowledge of the SQL statements for OLAP queries in a data warehouse. - Ability to write OLAP queries in the SQL language. - Knowledge of the major data mining algorithms for classification, clustering, and association rule mining.
- Knowledge of the main technological characteristics of a database management system: concurrent data access management, reliability, physical level structures, data access optimization. - Ability to design the physical data structures for a relational database. - Knowledge of distributed database system architecture and replication management. - Knowledge of active database systems and SQL statements for trigger definition. - Ability to write triggers in the SQL language. - Knowledge of data warehouse architecture and of the methodology for conceptual, logical, and physical design of a data warehouse. - Ability to design a data warehouse. - Knowledge of the SQL statements for OLAP queries in a data warehouse. - Ability to write OLAP queries in the SQL language. - Knowledge of the major data mining algorithms for classification, clustering, and association rule mining.
Knowledge of the relational model and SQL language and basic programming skills.
Knowledge of the relational model and SQL language and basic programming skills.
- Technological characteristics of a database management system: concurrent data access management, reliability, physical level structures, data access optimization (1.8 cr.) - Active database systems and SQL statements for trigger definition (0.4 cr.) - Distributed database system architecture and replication management (0.4 cr.) - Data warehouses: architecture, methodology for conceptual, logical, and physical design, SQL statements for OLAP queries (1.4 cr.) - Data mining algorithms: classification, clustering, and association rule mining (1.6 cr.)
- Technological characteristics of a database management system: concurrent data access management, reliability, physical level structures, data access optimization (1.8 cr.) - Active database systems and SQL statements for trigger definition (0.4 cr.) - Distributed database system architecture and replication management (0.4 cr.) - Data warehouses: architecture, methodology for conceptual, logical, and physical design, SQL statements for OLAP queries (1.4 cr.) - Data mining algorithms: classification, clustering, and association rule mining (1.6 cr.)
The course includes practices on the lecture topics, and in particular SQL language, physical database design, and conceptual, logical, and physical data warehouse design (1.8 cr.). Students will prepare an individual written report on exercises proposed during the course. The report will contribute to the final exam grade. The course includes laboratory sessions on the SQL language (also for database physical design) and data warehouse design (1.2 cr.). Laboratory sessions allow experimental activities on the most widespread commercial and open-source products.
The course includes practices on the lecture topics, and in particular SQL language, physical database design, and conceptual, logical, and physical data warehouse design (1.8 cr.). Students will prepare an individual written report on exercises proposed during the course. The report will contribute to the final exam grade. The course includes laboratory sessions on the SQL language (also for database physical design) and data warehouse design (1.2 cr.). Laboratory sessions allow experimental activities on the most widespread commercial and open-source products.
Reference books: - Atzeni, Ceri, Paraboschi, Torlone, 'Database systems', 1 ed., McGraw Hill, 1999. - Golfarelli, Rizzi, 'Data warehouse: teoria e pratica della progettazione', 2 ed., McGraw Hill, 2006. - Tan, Steinbach, Kumar, 'An introduction to data mining', Addison Wesley, 2005. Copies of the slides used during the lectures, examples of written exams and exercises, and manuals for the activities in the laboratory will be made available. All teaching material is downloadable from the course website or the Portal.
Reference books: - Atzeni, Ceri, Paraboschi, Torlone, 'Database systems', 1 ed., McGraw Hill, 1999. - Golfarelli, Rizzi, 'Data warehouse: teoria e pratica della progettazione', 2 ed., McGraw Hill, 2006. - Tan, Steinbach, Kumar, 'An introduction to data mining', Addison Wesley, 2005. Copies of the slides used during the lectures, examples of written exams and exercises, and manuals for the activities in the laboratory will be made available. All teaching material is downloadable from the course website or the Portal.
Modalità di esame: prova scritta; prova orale facoltativa;
The exam includes a written part, the evaluation of the reports on the individual practices assigned during the course, and an oral part. The individual practices and the oral part are optional. The written part lasts 2 hours. The final score is defined by considering the evaluation of the written part, and, optionally, of the individual practices and the oral part. The individual practices are considered only if the grade of the written part is 18 or above. Without the oral part, the maximum final grade given by the written part and the evaluation of the reports on the individual practices is 26. Otherwise, the final grade is the (approximated) average computed on the grade on the written part, the evaluation of the report on the individual practices, and the grade on the oral part. The written part includes - 2 multiple choice theory questions on the main course topics (technological characteristics of a database management system, SQL language, physical database design, conceptual, logical, and physical data warehouse design, data mining algorithms) (max 2 points) - 1 exercise on physical design (max 7 points) - 1 exercise on trigger design (max 8 points) - 1 exercise on data warehousing, including the design of a data warehouse and SQL queries for data access (max 13 points) Students can use textbooks or notes during the exam. Exercises are evaluated according to the correctness of the proposed solution and to the appropriateness of the adopted resolution methodologies. The oral part includes questions on the main topics of the lectures (max 30 points). Reports on the individual practices assigned during the course are on the main topics of the lectures (max 2 points).
Exam: written test; optional oral exam;
The exam includes a written part, the evaluation of the reports on the individual practices assigned during the course, and an oral part. The individual practices and the oral part are optional. The written part lasts 2 hours. The final score is defined by considering the evaluation of the written part, and, optionally, of the individual practices and the oral part. The individual practices are considered only if the grade of the written part is 18 or above. Without the oral part, the maximum final grade given by the written part and the evaluation of the reports on the individual practices is 26. Otherwise, the final grade is the (approximated) average computed on the grade on the written part, the evaluation of the report on the individual practices, and the grade on the oral part. The written part includes - 2 multiple choice theory questions on the main course topics (technological characteristics of a database management system, SQL language, physical database design, conceptual, logical, and physical data warehouse design, data mining algorithms) (max 2 points) - 1 exercise on physical design (max 7 points) - 1 exercise on trigger design (max 8 points) - 1 exercise on data warehousing, including the design of a data warehouse and SQL queries for data access (max 13 points) Students can use textbooks or notes during the exam. Exercises are evaluated according to the correctness of the proposed solution and to the appropriateness of the adopted resolution methodologies. The oral part includes questions on the main topics of the lectures (max 30 points). Reports on the individual practices assigned during the course are on the main topics of the lectures (max 2 points).


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