- Teaching in italian
- DATA MANAGEMENT
- DATA MANAGEMENT
- Subject area
- Reference degree course
- MANAGEMENT ENGINEERING
- Course type
- Master's Degree
- Teaching hours
- Frontal Hours: 81.0
- Academic year
- Year taught
- Course year
- Percorso comune
- Reference professor for teaching
- ZAPPATORE MARCO SALVATORE
The course prerequisites only refer to the basic usage of modern OSs and basic knowledge of the filesystem management procedures.
The course will be organised into four section:
- Management Information Systems
- Technical / technological aspects;
- Business aspects;
- Business Intelligence (BI) concepts;
- Enterprise MIS;
- The importance of data management and data quality.
- Relational Databases, R-DBMS and OLTP
- Introduction; core concepts and definitions; reference architectures
- Data, Database, DBMS, RDBMS
- Conceptual modelling: ER / EER diagrams and design reference patterns
- Logical modelling: the mapping algorithm
- Physical modelling
- SQL queries
- Introduction to NoSQL DBMS
- Data Warehouse (DWH) and OLAP
- Introduction; core concepts and definitions
- Requirement analysis and elicitation
- Use case modelling with UML 2.0 U-C diagrams
- Conceptual modelling: DFM
- Logical modelling: ROLAP
- Physical modelling: DWH and data marts
- ETL pipelines
- Additional topics
- Citizen Science
- Data security
- Data storytelling
- Data visualisation
- (Big) Data Quality
The course aims at introducing students to the data management domain, by focusing specifically on management information systems (MISs), database and data warehouse structure, functions and modelling. In addition, related topics will be examined as well, such as data visualisation and data storytelling, data quality and big data quality. The following learning objectives are considered:
- achieving the capability to identify featuring aspects of MISs
- learning what MIS architecture must be referred to depending on the specific business situation
- understanding how modern organisations manages information systems
- learning basic notions on databases and database management systems (DBMS)
- understanding the relational database theory
- understanding how to model a relational database from a conceptual and logical perspective
- learning how to use the SQL language to interact with a R-DBMS
- understanding multi-dimensional analysis and the DFM approach
- learning the differences between DBMS and DWH
- understanding the differences between OLAP and OLTP
- understanding the basic concepts of (big) data quality
- learning the basic notions of data visualisation and data storytelling
The course will be provided via frontal lessons and practical session. Students will be engaged in interactive lectures during which their data modelling abilities will be checked and nurtured.
A two-section exam is required:
- written exam [20 pts.]. It will consists of the following parts:
- Full data modelling exercise (a use case will be described in the exam text, along with some specific requirements, and the application of a given data modelling approach will be requested)
- 2 or 3 SQL queries (to be applied to the proposed data model)
- 2 or 3 open questions on theoretical aspects dealt with during the course
- project work [10 pts.]. The project work will be performed collaboratively, in teams. During the second half of the course, a set of potential use cases and related project works will be presented to students. Students will organize themselves into groups and each group will select one use case. All the project work proposals will be based on the application of theoretical contents to a concrete/mocked use case. In their project work, students will be asked to use at least some the software tools examined during the course. Once completed, the team will have to provide an online interactive presentation of the work done (i.e., Microsoft PowerPoint presentation + practical live session, via Microsoft Teams) of no more than 30'.
Please refer to the course team available in Microsoft Teams.
 Baltzan, P. (2022). M: Information Systems (6th Ed.). McGraw Hill Education (US).
 Elmasri, R., Navathe, S.B. (2016). Fundamentals of Database Systems (7th Ed.). Pearsons.
 Golfarelli, M., Rizzi, S., (2009). Data Warehouse Design: Modern Principles and Methodologies. McGraw Hill Education (Europe).
 Additional teaching materials supplied by the teacher.
First Semester (dal 20/09/2021 al 17/12/2021)
Type of assessment
Oral - Final grade