Table of Contents

Technologies for Big Data Management


News

  • Exam results 09/09/2024: result are available here.
  • Exam update, 09/09/2024:: exam is planned at 15:00 in AB2
  • Exam results 08/07/2024: result are available here.
  • Exam results 24/06/2024: result are available here.
  • Exam results 26/02/2024: result are available here.
  • Exam results 12/02/2024: result are available here.
  • Exam results 01/02/2024: result are available here.
  • Exam update, 1st of February - 14:00:: exam is planned in AB1.
  • Course completed: the next 8th of January 2024 there will be a meeting in which we are going to discuss the writing exam, to do a check on the ongoing projects, etc. The meeting is scheduled at 14:00, room LB1.
  • No lesson the 11th of December: no lesson on this day.
  • Projects: the list of the project is available at the following link.
  • No lesson the 30th of October: no lesson on this day.
  • No lesson the 23th of October: no lesson on this day.
  • TBDM on Telegram: students can join to the Telegram group with the following link.
  • Course delayed: the course is planned to start the 9th of October - LB1.

General Info

Teacher:

ESSE3 Link

Scheduling of Lectures:

  • Scheduling is available at the following link

Degrees:


Course Objectives

  • 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.

Syllabus

  • 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.

Study material

Course Slides

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

Exams

Exam Dates A.Y. 2023/2024 (tentative)

  • 01/02/2024
  • 12/02/2024
  • 26/02/2024
  • 24/06/2024
  • 08/07/2024
  • 29/07/2024
  • 09/09/2024
  • 02/12/2024
  • 10/02/2025
  • 24/02/2025

Exam rules:

  • Writing Examination
  • Project lab (max 3 member per team)

For the 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. future improvements

Exam Results

  • See news section