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Business Intelligence and Applications


Martinenghi D.

Course director

Alchieri L.



The first part of the course addresses core topics, such as enterprise data integration, visualization, and data mining. The second part gives an outlook on emerging data architectures, including social network structures and Big Data analytics. 

Course outline:

  • Data management architectures.
  • OLAP and OLTP.
  • Data warehouse architecture and design.
  • Data Mining: clustering, classification, association rules.
  • Visualization.
  • Networks: models and centrality measures.
  • A selection of topics among Big Data, NoSQL databases, ranking.


The course develops a working knowledge of the principles, architectures, and tools for Business Intelligence.

Teaching mode

In presence

Learning methods

Besides traditional classroom-taught lectures, the course include discussions with students, live demos of tools, presentation of groupwork, and homework with individual assignments.

Examination information

The evaluation consists of:

  • a written midterm test;
  • a written final test;
  • several small project assignments.