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Tecnologie per i Sistemi Informativi (IA)
Technologies for Information Systems
Claudia Diamantini

Seat Ingegneria
A.A. 2016/2017
Credits 9
Hours 72
Period II
Language ENG

Prerequisites
Models and languages for relational database management, basic concepts of algebra e logics, basic concepts of probability theory

Learning outcomes
KNOWLEDGE AND UNDERSTANDING:
The course enables students to acquire advanced knowledge on the management and analysis of data in centralized and distributed environments. In particular: logical models, architectures and methodologies for the design and management of Big Data in modern distributed information systems, understaning advantages and limitations of the different solutions; data base management systems technologies both in a centralized and distributed environment; models and techniques for Business Intelligence and Data Analytics (multidimensional model and OLAP analysis, DataWarehouse, Data Mining techniques).
CAPACITY TO APPLY KNOWLEDGE AND UNDERSTANDING:
The student will be able to use and configure in an advanced way database management systems, to design and manage the distribution of data in the most suitable manner for the particular application context, ensuring efficiency, flexibility, autonomy and cost containment, to extract knowledge from data evaluating the quality of results.
TRANSVERSAL SKILLS:
The development of a project that will be done in small groups, and that will lead to the writing and presentation of a report, will help to improve student's ability to make judgments as well as the ability to communicate that also stems from teamworking. Along with the study based on different materials this will also help developing student's learning and synthesis skills.

Program
- Technologies for centralized data management: physical organization of data on secondary storage, DBMS architecture, query management, transaction processing management. - Architectures for the manamagement of data in distributed information systems: distributed DBMS, fragmentation and allocation, transparency, elements of distribution design. Federated DBMS, database integration. - Technologies for distributed data management: distributed query and transaction processing. Big Data management in cloud systems: NoSQL models, replication and inconsistency, CAP theorem. - Business Intelligence e Data Analytics: datawarehouse architecture and multi-dimensional model, data warehouse design, Data Mining.

Development of the examination
LEARNING EVALUATION METHODS
Evaluation is based on two tests: - The development of a project or term paper in which the student deepens one of the topics of his interest. The project can be done in groups, composed of a maximum of three students. For the development of the projects periodic reviews are planned, in which students are required to organize an oral presentation of the project results, and the production of a report documenting the activities undertaken and the results obtained. - An oral exam, consisting of the exposition of concepts and theoretical aspects on one or more topics covered in the course. The two tests can be performed in any order.

LEARNING EVALUATION CRITERIA
To successfully pass the assessment of learning, the student must demonstrate, through the tests described above, a good understanding of the concepts presented in the course on technologies for the management of information systems and must demonstrate the capability of personal reflection and deepening, critical thinking and problem solving abilities in the execution of project activities.

LEARNING MEASUREMENT CRITERIA
During the tests it is assessed the degree of completeness and depth achieved in knowledge and understanding of the issues. It is also assessed the ability to use in a correct and autonomous way models and methodologies for solving problems.

FINAL MARK ALLOCATION CRITERIA
For the first test a maximum of 6 points are awarded for projectual/experimental activities, and a maximum of 4 points to survey reports summarizing others studies, comparing results an so on. This score is added to the marks obtained in the oral exam, which ranges between zero and 24, for an overall grade ranging between zero and 30. In order for the overall outcome grade to be positive, the student must achieve a pass, equal to 15 points in the oral test, demonstrating a basic level of knowledge and understading on the topics covered in the test, and a score greater than zero in the project, linked to the achievement of the objectives set. The highest rating is achieved by demonstrating a thorough understanding of the course content and excellent ability to carry out the project. The praise is reserved for students who have demonstrated a particular brilliance in oral exposure and development of the project.

Recommended reading
- P. Atzeni, S. Ceri, S. Fraternali, S. Paraboschi, R. Torlone, “Basi di Dati: architetture e linee di evoluzione“, McGraw-Hill. - M.T. Özsu and P. Valduriez, “Principles of Distributed Database Systems, 2nd edition“, Prentice-Hall - Further material provided by the teacher on the course site hosted by the University learning management system, https://lms.univpm.it

Courses

• Ingegneria Informatica e dell'Automazione (Corso di Laurea Magistrale (DM 270/04))