IoT and Data Analytics

  • 25/09/2019: The course page is online.


  • TBD

ESSE3 Link

  • TBD

Lessons schedule:

  • TBD 2nd semester

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

  • Slides link
    • Course introduction and rules
    • Enterprise Data Analytics
    • Big Data
    • Storage & Computation
    • NoSQL
    • Computation
    • Analytics lab with Apache Spark, Cassandra, PySpark
    • Data Analytics models
  • Reference materials
  • Slides course.
  • Material provided by the teacher.
  • Examples
  • Other materials

Exam Dates A.Y. 2019/2020

  • TBD

Exam rules:

  • Writing Examination on the topics of the course
    • Open or multiple-choice questions + Exercise
    • 2 h
  • Project lab (max 2 member per team)

Project files:

  • TBD

Exam Results

  • -