Skip to main content
If you continue browsing this website, you agree to our policies:
  • Condizioni di utilizzo e trattamento dei dati
Continue
x
e-Learning - UNIMIB
  • Home
  • My Media
  • More
Listen to this page using ReadSpeaker
 Log in
e-Learning - UNIMIB
Home My Media
Percorso della pagina
  1. Science
  2. Master Degree
  3. Data Science [FDS02Q - FDS01Q]
  4. Courses
  5. A.A. 2024-2025
  6. 2nd year
  1. Business Intelligence and Big Data Analytics
  2. Summary
Insegnamento Course full name
Business Intelligence and Big Data Analytics
Course ID number
2425-2-FDS01Q037
Course summary SYLLABUS

Course Syllabus

  • Italiano ‎(it)‎
  • English ‎(en)‎
Export

Obiettivi formativi

Contenuti sintetici

Programma esteso

Prerequisiti

Metodi didattici

Modalità di verifica dell'apprendimento

Testi di riferimento

Periodo di erogazione dell'insegnamento

Lingua di insegnamento

Sustainable Development Goals

IMPRESE, INNOVAZIONE E INFRASTRUTTURE
Export

Learning objectives

The course will cover both methodological and technical aspects necessary to understand and implement Business Intelligence (BI) and Big Data Analytics (BDA) solutions in real-world contexts. It will address the evolution of BI architectures, decision models based on business functions, and big data architectures such as data lakes and lakehouses. Additionally, the course will explore AI techniques for supporting decisions, including explainable AI (XAI) and conversational AI using word embeddings and large language models (LLMs). The course will provide the foundations to understand, evaluate, and implement BI and BDA solutions, as well as to comprehend the differences between the two.

Contents

  1. Introduction to BI and Big Data Analytics
  2. BI Architectures
  3. Big Data Analytics
  4. AI for supporting decisions

Detailed program

  1. Introduction to BI and Big Data Analytics
    a. Goal and rationale of BI systems
    b. The value of knowledge – digital economy and data-driven decision making
    c. The Structure and subsequent evolution of BI and Big Data Analytics systems

  2. BI Architectures
    a. The Evolution of BI Architectures (towards Big Data)
    b. Decision Models based on business functions and type of decisions

  3. Big Data Analytics
    a. Data lake and lakehouse
    b. Big data architectures to scale-out (pyspark)

  4. AI for supporting decisions
    a. Explainable and Evaluative AI
    b. Explainers (LIME, SHAP, Anchors, ContrXT...)
    c. Conversational AI and XAI via word embeddings and LLMs

Prerequisites

None

Teaching methods

The course will be provided by means of lessons, seminars, laboratory sessions, and homework.

Assessment methods

written examination

Textbooks and Reading Materials

Lectures with the support of slides, laboratory and real-life case studies. Scientific Papers and books indicated by the lecturer. The software used is either available as open-source

Semester

I semester

Teaching language

English

Sustainable Development Goals

INDUSTRY, INNOVATION AND INFRASTRUCTURE
Enter

Key information

Field of research
INF/01
ECTS
6
Term
First semester
Activity type
Mandatory to be chosen
Course Length (Hours)
46
Degree Course Type
2-year Master Degreee
Language
English

Staff

    Teacher

  • LM
    Lorenzo Malandri
  • Fabio Mercorio
    Fabio Mercorio

Students' opinion

View previous A.Y. opinion

Bibliography

Find the books for this course in the Library

Enrolment methods

Self enrolment (Student)
Manual enrolments

Sustainable Development Goals

INDUSTRY, INNOVATION AND INFRASTRUCTURE - Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
INDUSTRY, INNOVATION AND INFRASTRUCTURE

You are not logged in. (Log in)
Policies
Get the mobile app
Powered by Moodle
© 2025 Università degli Studi di Milano-Bicocca
  • Privacy policy
  • Accessibility
  • Statistics