98060 - Extracting and organising data from complex sources

Learning outcomes

At the end of the course, the students will have acquired theoretical knowledge and practical competencies about the most common models and architectures for the digital representation of data, their structure and the type of problems that each data format solves and does not solve. They will have learnt the use of state- of-the-art tools to create pipelines to extract and organize data for simple applications of data analytics.

Course contents

Data, encodings and data structures

1. Table data
2. Structured data
3. Text data

Data processing processes

1. Reading data
2. Selecting and extracting data
3. processing and transforming data
4. data visualization and exporting

Data Analytics Platforms

1. Knime Analytics Platform

Readings/Bibliography

Course Slides and online reading material provided during classes

Teaching methods

Classes in presence and laboratory practice

Assessment methods

Project work for the processing of data in groups of 2-3 individuals

Teaching tools

1. Digital laboratory
2. Software KNIME for data analytics 

Office hours

See the website of Fabio Vitali

See the website of Angelo Di Iorio