Information management

A.Y. 2017/2018
Lesson for
6
Max ECTS
48
Overall hours
Language
English
Learning objectives
- to understand the data collection, integration, processing, analysis and visualization issues as an integrated process
- to be introduced to the main methodological and practical tools for data mining and data analytics
- techniques for data quality evaluation and preprocessing
- techniques for numerosity and dimensionality reduction in data;
- methods for frequent pattern analysis and association rules;
- methods for classification problems;
- cluster analysis;
- R language programming.

Course structure and Syllabus

Active edition
Yes
Responsible
Lessons: 48 hours
Professor: Ceselli Alberto
Syllabus
The Information Management course aims at presenting the whole data journey as an integrated process. In particular, for each of the following steps, suitable methodologies are reviewed and compared: (a) data collection and statistical analysis, (b) data integration, (c) data governance, quality assessment and improvement, (d) data analytics, (e) data visualization.
The core of the course is devoted to data analytics, and in particular to the advanced information management techniques that are collectively known as data mining. These techniques are oriented toward the automatic or semi-automatic extraction of knowledge from big data.
Lesson period
First semester
Lesson period
First semester
Assessment methods
Esame
Assessment result
voto verbalizzato in trentesimi
Professor(s)