From Big Data to Data Platform - Research and Challenges

This PhD course discusses the transition from big data architectures to the broader notion of data platforms and introduces some of the research opportunities and open challenges around this topic.

It is held within the PhD in Computer Science and Engineering at the University of Bologna.

Program

The course is subdivided into three parts. In the first part, an introduction to the world of big data is given, so as to bring up to speed the students that have no prior knowledge on the subject. In the second part, an in-depth analysis of the polyglot persistence theme is given, introducing the concepts of multistores and polystores and the techniques to query heterogeneous distributed database systems. In the last part, the metadata challenge is presented to discuss the main issues related to metadata generation, maintenance, and exploitation.

(Course material will be published here).

Schedule

The course is held at the Cesena Campus (via dell’Università, 50). Students that cannot physically attend the course can join online via Microsoft Teams (links will be published here).

Duration: 10 hours

Exam

Students requiring an exam will be asked to produce an essay about possible intersections between their research interests and the topics/open issues presented in this course.

Participation

Students willing to follow the course are kindly asked to send a notification of interest to the teacher by the end of the year, indicating (i) existing issues with the indicated schedule (if any), (ii) the background level on big data, and (iii) whether the course will be followed online or in presence. The notification is neither binding nor required, but it is asked for organization purposes.

Teacher

Enrico Gallinucci is Junior Assistant Professor at the University of Bologna, Cesena. He teaches Big Data and Business Intelligence at the Master’s Degree in Computer Science and Engineering. His research activities are focused on the topics of big data, NoSQL databases, social and conversational business intelligence, trajectory data analysis, precision agriculture.