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Scheda Riassuntiva
Anno Accademico 2016/2017
Tipo incarico Dottorato
Insegnamento 096700 - A MULTIDISCIPLINARY 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 DOTTORATOAZZZZ096700 - A MULTIDISCIPLINARY PERSPECTIVE ON BIG DATA

Programma dettagliato e risultati di apprendimento attesi

LECTURERS

Responsible : Emanuele Della Valle

Lectures:  Danilo Ardagna, Michela Arnaboldi, Paolo Ciuccarelli, Emanuele Della Valle, Simone Vantini

Other Lecturers: Marco Brambilla, Cinzia Cappiello, Stefano Ceri, Paolo Cremonesi, Elisabetta Di Nitto, Piero Fraternali, Pierlunca Lanzi, Letizia Tanca, Telecom Italia Big Data expert (to be identified), IBM Big Data expert (to be identified), Oracle Big data expert (to be identified)

MISSION AND GOALS

The term Big Data refers to a growing torrent of information that, if successfully analyzed, can unleash new business opportunities and revenues. This course aims at introducing Big Data analytics methods and includes practical sessions on PoliMI’s Big Data computational infrastructure.

CLASSES

Introduction to big data (1 hour)                   

  • What is Big Data? volume, velocity, variety, veracity, … to create value
  • Paradigm shifts enabled

Mastering the volume dimension (5 hours) 

  • Introduction to cloud computing and Technologies for Infrastructure-as-a-Service
  • NoSQL databases for Big Data   
  • Map Reduce from Hadoop to Spark and Flink

Mastering the variety dimension (2 hours)

  • Data Integration principles, approaches and tools       
  • The role of Ontologies and Semantic Web technologies

Mastering the velocity dimension (2 hours)

  • Information flow processing principle, approaches and tools         
  • velocity for Big Data with Spark and Flink 

Mastering the veracity dimension (2 hours)                                    

  • data quality, definitions, dimensions, approaches and tools
  • uncertainty and data quality problems in big data

Making sense of Big Data (8 hours)

  • introduction to data analytics with the R language
  • knowledge discovery and Data Mining
  • Visual analytics        

Creating Value with Big Data (3 hours)

  • dimension and structure of the Big Data Market
  • organizational issues in Big Data project (skills, processes, success/failure factors)

Open Workshop on Big Data (4 hours)                                              

  • genomics applications (PoliMI)
  • cognitive computing (IBM)                                            
  • multimedia analytics (PoliMI)                                        
  • Mobile Telefone Data Analytics (Telecom Italia)
  • Social Media Analytics (PoliMI)                                     
  • Big Data in the Oil and Gas Industry (Oracle)


TEACHING MATERIALS

The course material consists in slides prepared by the lecturers, links to on-line tutorials, and the dataset of Telecom Italia Big Data Challenge (http://www.telecomitalia.com/tit/en/bigdatachallenge/contest.html). Students will gain enough background on the topics to be able to use the infrastructure made available by IBM as well as the poliCloud one donated by Yahoo!.


Note Sulla Modalità di valutazione

The exams will consist in reporting the experience in using the tools and in discussing the different trade-offs offered by them. The reporting exercise will be organised in three tracks: one focus on business value, one on analytics and one on visualisation.


Intervallo di svolgimento dell'attività didattica
Data inizio
Data termine

Calendario testuale dell'attività didattica

We have reserved the following days in the calendar for the following points. A more precise calendar will be available by the day of the first lecture

  • Introduction to big data and data base fundamentals (3h)
    • 1.3.2017 - 10:00-13:00 in the Seminar Room of building 20 prof. Della Valle and prof. Tanca
  • Mastering the volume dimension (5h)
    • 8.3.2017 - 9:30-11:00 in the Conference Room of building 20 prof. Cremonesi
    • 8.3.2017 - 14:30-16:30 in the Conference Room of building 20 prof. Ardagna
    • 9.3.2017 - 10:00-12:00 in the Seminar Room of building 20 prof. Di Nitto
  • Mastering the variety, velocity and variety dimensions (6h)
    • 14.3.2017 - 10:00-13:00 in the Conference Room of building 20 prof. Della Valle and prof. Tanca
    • 16.3.2017 - 10:00-12:00 in the Conference Room of building 20 prof. Della Valle
    • 16.3.2017 - 14:30-16:30 in the Conference Room of building 20 prof. Cappiello
  • Making sense of Big Data (8h)
    • 21.3.2017 - 10:00-12:00 in the Seminar Room of building 20 prof. Ciuccarelli
    • 22.3.2017 - 10:00-12:00 in the Conference Room of building 20 prof. Lanzi
    • 23.3.2017 - 10:00-13:00 in the Conference Room of building 20 prof. Vantini
  • Creating Value with Big Data (3 hours)
    • 31.3.2017 - 10:00-13:00 in the Seminar Room of building 20 prof. Arnaboldi
  • Open Workshop on Big Data (4h)
    • to be confirmed

 


Bibliografia

Mix Forme Didattiche
Tipo Forma Didattica Ore didattiche
lezione
27.0
esercitazione
0.0
laboratorio informatico
0.0
laboratorio sperimentale
0.0
progetto
60.0
laboratorio di progetto
0.0

Informazioni in lingua inglese a supporto dell'internazionalizzazione
Insegnamento erogato in lingua Inglese

Note Docente
19/11/2018 Area Servizi ICT v. 1.4.11 / 1.4.11