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Enterprise Data Analytics

News

Exam Partial 1: results are available here.

Material update: Other materials section updated with EDA projects A.Y 2018-19.

Project update: projects and IoT dataset have been updated.

Project update: a draft of available projects is available here.

Google meet: due to some possible problems with Webex, lesson will be done via Google Meet. Instruction here. Room name edaunicam2020.

Course start: the first lesson is planned for 12th of March 2019, only via webex room.

General Info

Teacher:

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

ESSE3 Link

  • —

Webex Link

Lessons schedule:

  • 42 h - lectures, exercise sessions
  • Schedule on Thursday from 14:00am to 18:00pm
  • LB1 room
  • Schedule (tentative)
    1. 12-mar-20 - 14:00-18:00
    2. 19-mar-20 - 14:00-18:00
    3. 26-mar-20 - 14:30-17:30
    4. 02-apr-20 - 14:00-18:00
    5. 09-apr-20 - 14:00-18:00
    6. 16-apr-20 - 14:00-17:00
    7. 23-apr-20 - 14:00-18:00
    8. 30-apr-20 - 14:30-17:30
    9. 07-mag-20 - 14:00-18:00
    10. 14-mag-20 - 14:00-18:00
    11. 21-mag-20 - 14:00-18:00
    12. 28-mag-20 - 14:30-16:30

Students Office hours:

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

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.

Course Contents

  • 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.

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

Exams

Exam Dates A.Y. 2019/2020 (tentative)

  • 06/18/2020
  • 07/09/2020
  • 07/30/2020
  • 09/03/2020
  • 10/01/2020
  • 10/22/2020
  • 12/10/2020
  • 01/14/2021
  • 02/11/2021

Exam rules:

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

Exam Results

  • -