Table of Contents

Technologies for Big Data Management

News

  • Exam results 09/01/2024: result are available here.
  • Exam results 26/05/2023: result are available here.
  • Exam of 26th of May update: the exam will be held in AB3 room from 14:30.
  • Exam results 27/02/2023: result are available here.
  • Exam results 20/02/2023: result are available here.
  • Exam results 09/02/2023: result are available here.
  • Lecture update: next lecture will be the 16th of January.
  • No lecture 16/12/2022: next lecture will be the 19th of December.
  • No lecture 02/12/2022: next lecture will be the 5th of December.
  • Projects update: projects can be found at the following link (in progress)
  • Lectures update: next lecture will be the 11th of October. No lesson the 7th of November.
  • Lectures update: next lecture will be the 24th of October.
  • Lectures suspended: lectures are suspended until new communications.
  • No lecture 07/10/2022: next lecture will be the 10th of October.
  • TBDM on Telegram: students can join to the Telegram group with the following link.
  • Slides: course material can be found here.

General Info

Teacher:

ESSE3 Link

Scheduling of Lectures:

  • Scheduling is available at the following link
  • 42 h - lectures, exercise sessions
  • Schedule on: Monday 14:00-17:00 and Friday 14:00-17:00, AB1 at Polo Ludovici

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

  • Projects A.A. 2021/22 - link
  • Projects A.A. 2020/21 - link
  • Reference materials
    • Slides course.
    • Material provided by the teacher.
    • Examples
      • …
    • Other materials
      • …

Exams

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

  • 09/02/2023
  • 20/02/2023
  • 27/02/2023 at 13:00 (new added)
  • 26/05/2023
  • 16/06/2023
  • 21/07/2023
  • 08/09/2023
  • 25/09/2023
  • 09/02/2024
  • 20/02/2024

Exam rules:

  • Writing Examination on the topics of the course
  • 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