Data Analytics

* Exam 22/03/2021 update: exam results with the writing vote are available here

* Exam update (only valid for session date 22th of march 2021) : exam rules are available here. Note that exam will be done via Webex and students must have Acrobat Reader installed.

* Exam update for the 22th of march 2021: exam session is scheduled at 10:00am only in webex.

* Projects update:projects list has been updated with source code and slides links.

* Project discussion update: for the project discussion students have to publish the final code to a public github repository (or similar) along with the necessary documnatation (pre-requisite, installation, configuration, usage, etc). Moreover a set of slides have to be presented in that day along with a practical demonstration of the running code. Slides should cover the following points:

  1. Project description / objectives
  2. Methodology and technology being used
  3. Technical implementation
  4. Achieved results
  5. Possible future improvements

* Exam update: an additional exam session has been scheduled for the 22th of march 2021.

* Project update: students that are ready to discuss the project are invited to contact the professor to arrange a date for the presentation.

* Exam 22/02/2021 update: exam results with the writing vote are available here

* Exam 01/02/2021 update: exam results with the writing vote are available here

* Exam 01/02/2021 update: exam results are available here

* Exam update: session confirmed for the 1th of february at 14:00, AB2 classroom - Polo Ludovici.

* Exam rule clarification: online exam session is planned. Interested students have to compile the corresponding module.

* Exam rule clarification: only students signed on ESSE3 will be allowed to do the exam.

* Exam rule clarification: students can do the writing exam and present the project later on.

* Avvio rilevazione delle opinioni e della soddisfazione degli studenti, aa 2020/21: students are invaited to submit the survey.

* Projects update: projects list updated Link.

* No lecture 09/11/2020: lecture suspended.

* No lecture 16/10/2020: lecture suspended.

* Course start: the first lesson is planned for 2th of October 2020, at Polo Ludovici (LB1) - online streaming via webex.


  • Dr. Massimo Callisto De Donato <massimo.callistodedonato[at]>

ESSE3 Link

Webex Link

Lessons schedule:

  • 42 h - lectures, exercise sessions
  • Schedule on: Monday/Friday 14:00am to 16:00pm
  • LB1 room-new Polo Ludovici
  • Schedule (tentative)
    • 02,05,09,12,16,19,23,26,30/10/2020
    • 06,09,13,16,20,23,27,30/11/2020
    • 04,11,14,18,21/12/2020

Students Office hours:

  • Send an e-mail to the teacher to fix an appointment.

  • knowledge about business data analysis and modern scenarios such as the Internet of Things.
  • Understanding of main differences between classical methods in data analysis and new modern scenarios.
  • Knowledge and expertise on Big Data methodologies and technologies, basic principles and concepts, techniques that enable data analysis and management.
  • Knowledge of the main Big Data technological frameworks and application in real case studies.
  • Highlight some Intelligent Data Analysis techniques.

  • Acquire knowledge and competence on Big Data methodologies, techniques and technologies.
  • Know most common techniques of Big Data analysis and how they apply to real world examples.
  • Apply Big Data Analysis techniques into practical case studies.

  • Introduction to enterprise and data management.
  • Analysis of scenarios and contexts of data generation: from the inter-organizational model to the Internet of things.
  • Introduction to the classic data analysis techniques: ETL (Extract, Transform, Load), Business Intelligence, Reporting Tools.
  • Methodologies and technologies for the management and analysis of large amounts of data: introduction to the Big Data model, concepts, principles and technological frameworks.
  • Data Analytics methodologies and techniques: batch analysis models, streaming computation.
  • Data Analytics evolution towards intelligent data understanding models.

Course Slides

  • Reference materials
    • Slides course.
    • Material provided by the teacher.
    • Examples
    • Other materials

Exam Dates A.Y. 2020/2021 (tentative)

  • 01/02/2021
  • 22/02/2021
  • 22/03/2021
  • 07/06/2021
  • 28/06/2021
  • 26/07/2021
  • 06/09/2021
  • 15/11/2021
  • 20/12/2021
  • 07/02/2022

Exam rules:

  • Writing Examination on the topics of the course
  • Project lab (max 2 member per team)

Exam Results