The course aims to examine the relationship between law, rights and new technologies. Rights are born with man. The history of man should be read as a progressive struggle for rights. Now that new technologies have transformed society, the economy, the form of state and government, the life of man, it is necessary to reflect on how to guarantee rights, through law. Law must use the algorithmic systems, shaping them to values and constitutional values.
teacher profile teaching materials
date schedule topics room
06/10/25 18-20 Presentation of the course and training objectives 248
07/10/25 18-20 New Paradigms for Data Architectures 248
08/10/25 18-20 Emerging Issues - Data Privacy/Data Governance 383
13/10/25 18-20 GDPR: Regulations - GDPR: Roles 248
14/10/25 18-20 Data Analysis & Design: W6H 248
15/10/25 18-20 Data Modeling - ER 383
20/10/25 18-20 ER: Identification Keys + Exercise 248
21/10/25 18-20 ER: Hierarchies + Exercise 248
22/10/25 18-20 Exercise + Introduction to Data Warehouse 383
27/10/25 18-20 Data Warehouse-Multidimensional Model 248
28/10/25 18-20 Big Data: Definition 248
29/10/25 18-20 Big Data: NO Sql models 383
03/11/25 18-20 Analysis Feedback from Students+Basic Concepts Review 248
04/11/25 18-20 Big DataPicture: Data->Information->Knowledge->A.I. 248
05/11/25 18-20 Public Administration Digitalization: Italian Regulatory Agency 383
10/11/25 18-20 Big Data: AI 248
11/11/25 18-20 Big Data: ML and Deep Learning 248
12/11/25 18-20 Big Data: Use Cases 383
17/11/25 18-20 Review Course Topics + Exercise 248
18/11/25 18-20 Review Course Topics + Exercise 248
Programme
BIG DATA AND DECISIONS AUTOMATIONdate schedule topics room
06/10/25 18-20 Presentation of the course and training objectives 248
07/10/25 18-20 New Paradigms for Data Architectures 248
08/10/25 18-20 Emerging Issues - Data Privacy/Data Governance 383
13/10/25 18-20 GDPR: Regulations - GDPR: Roles 248
14/10/25 18-20 Data Analysis & Design: W6H 248
15/10/25 18-20 Data Modeling - ER 383
20/10/25 18-20 ER: Identification Keys + Exercise 248
21/10/25 18-20 ER: Hierarchies + Exercise 248
22/10/25 18-20 Exercise + Introduction to Data Warehouse 383
27/10/25 18-20 Data Warehouse-Multidimensional Model 248
28/10/25 18-20 Big Data: Definition 248
29/10/25 18-20 Big Data: NO Sql models 383
03/11/25 18-20 Analysis Feedback from Students+Basic Concepts Review 248
04/11/25 18-20 Big DataPicture: Data->Information->Knowledge->A.I. 248
05/11/25 18-20 Public Administration Digitalization: Italian Regulatory Agency 383
10/11/25 18-20 Big Data: AI 248
11/11/25 18-20 Big Data: ML and Deep Learning 248
12/11/25 18-20 Big Data: Use Cases 383
17/11/25 18-20 Review Course Topics + Exercise 248
18/11/25 18-20 Review Course Topics + Exercise 248
Core Documentation
The lessons will be available on the e-learning platform of the UniversityReference Bibliography
"Building the Data Lakehouse" Bill Inmon, Mary Levins, Ranjeet Srivastava - First Printing 2021 Copyright © 2021 by Bill Inmon, Mary Levins, and Ranjeet Srivastava ISBN, print ed. 9781634629669 ISBN, Kindle ed. 9781634629676 ISBN, ePub ed. 9781634629683 ISBN, PDF ed. 9781634629690 "Domain-Driven Design: Tackling Complexity in the Heart of Software" Eric Evans Addison-Wesley Professional First Printing 2004 ISBN: 0321125215 "The Entity Relationship Model — Toward a Unified View of Data" Peter_Pin_Shan-Chen Massachusetts Institute of Technology, USA © 2002 Springer-Verlag Berlin Heidelberg Print ISBN: 978-3-642-63970-8 "SMEData - Il diritto alla protezione dei dati personali: tra disciplina europea e adeguamento della disciplina nazionale" Università degli Studi Roma Tre - Dipartimento di Giurisprudenza Progetto cofinanziato dal Programma "Rights, Equality and Citizenship" della Unione EuropeaType of delivery of the course
The lessons will be supported by material that will be distributed at the end of each topic. The didactic approach will be oriented towards discussion and comparison on the topics that will be treated; therefore, the active participation of students in lessons will be particularly useful, to make the acquisition and consolidation of the notions learned more effective. The focus of the course will be centered on the functional understanding of the topics covered, highlighting the relationship between the use cases and the various classes of methods and tools presented, reserving an exposure to technologies oriented towards understanding their use rather than knowledge of the aspects of software engineering.Attendance
frequency is advisableType of evaluation
Students will be assessed on the basis of the acquired ability to describe the fundamental rationales of the design of BIG DATA solutions oriented to the analysis of complex phenomena for decision support, relating the methods and models covered by the course with the main classes of use cases.