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Scheda Riassuntiva
Anno Accademico 2018/2019
Tipo incarico Dottorato
Insegnamento 053949 - A TRANSDISCIPLINARY PERSPECTIVE ON BIG DATA
Docente Della Valle Emanuele
Cfu 5.00 Tipo insegnamento Monodisciplinare

Corso di Dottorato Da (compreso) A (escluso) Insegnamento
MI (1300) - SCUOLA DI DOTTORATOAZZZZ053949 - A TRANSDISCIPLINARY PERSPECTIVE ON BIG DATA

Programma dettagliato e risultati di apprendimento attesi

MISSION AND GOALS

Big data is everywhere and researchers from all disciplines are addressing this topic from their own perspective, creating vertical excellent experiments, but often loosing the wider picture. This course aims at reconstructing such a picture critically analysing how each discipline contributes to practice and academic debate.

LECTURERS

Proposer and Coordinator: Emanuele Della Valle

Team:
• DEIB: Danilo Ardagna, Marco Brambilla, Emanuele Della Valle and Pierluca Lanzi
• DIG: Michela Arnaboldi and Fabio Pammolli
• DMAT: Piercesare Secchi and Simone Vantini
• DESIGN: Paolo Ciuccarelli
• DASTU: Valeria Fedeli

TEACHING ORGANIZATION

The course is divided in 3 parts. The 1st provides a transversal view on grand challenges to which big data can contribute and allows understanding what big data is. The 2nd one presents the main paradigms and techniques for data analytics. The 3rd one teaches how practically tame volume, variety, velocity, and veracity.

SUBJECT AND PROGRAMME OF THE COURSE

Part 1: Grand challenges of Big Data

- Opportunities for social, environmental and economic problems.
- Problem of current research: lack of transversal view.
- Students define a transdisciplinary research objective, highlighting their contribution to practice and academic debate. This initial work is the starting point for the assignment and a fil-rouge across the course.

Part 2: Making sense of Big Data

- Introduction to data analytics with the R language
- Knowledge discovery and Data Mining
- The role of visualization
- Discussion of domain applications and students’ transdisciplinary assignments

Part 3: Taming volume and velocity, without forgetting variety and veracity with Big Data technologies

- Scaling computation and storage horizontally
- Map Reduce basics from Hadoop to Apache Spark and Flink
- Information flow processing principle, approaches and tools
- Hands-on Apache Spark to tame volume and velocity in data analytics
- Discussion of domain applications and students’ transdisciplinary assignments

Part 4: students’ reporting

 

 


Note Sulla Modalità di valutazione

Students will be required to build a research case, identifying business value, data and methods, using the tools to analyze and visualize data, critically analyzing pitfalls, and highlighting their contributions.


Intervallo di svolgimento dell'attività didattica
Data inizio
Data termine

Calendario testuale dell'attività didattica

Tentatively the course will take place in January 2019. The calendar will be published on the course's homepage (http://emanueledellavalle.org/teaching/phd-course-on-a-transdisciplinary-perspective-on-big-data/)


Bibliografia

Mix Forme Didattiche
Tipo Forma Didattica Ore didattiche
lezione
30.0
esercitazione
0.0
laboratorio informatico
0.0
laboratorio sperimentale
0.0
progetto
40.0
laboratorio di progetto
0.0

Informazioni in lingua inglese a supporto dell'internazionalizzazione
Insegnamento erogato in lingua Inglese
Disponibilità di materiale didattico/slides in lingua inglese
Possibilità di sostenere l'esame in lingua inglese
Disponibilità di supporto didattico in lingua inglese

Note Docente
The homepage of the course is http://emanueledellavalle.org/teaching/phd-course-on-a-transdisciplinary-perspective-on-big-data/
schedaincarico v. 1.6.1 / 1.6.1
Area Servizi ICT
08/12/2019