Data Analytics

* Exam 06/09/2021 update: exam results with the writing vote are available here

* Exam 26/07/2021 update: exam results with the writing vote are available here

* Exam 26/07/2021 update: exam session has been delayet. New session date: 30/07/2021.

* Exam 28/06/2021 update: exam results with the writing vote are available here

* Exam rules update: students must confirm their presence to the next exam sessions at least 5 days before the exam date. Confirmation must be send to by mail to the teacher, esse3 registration is not sufficient.

* Exam 28/06/2021 update: interested students for this session must send a mail to the teacher in order to do the exam.

* 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:

Project description / objectives
Methodology and technology being used
Technical implementation
Achieved results
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.

Teacher:

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

ESSE3 Link

—

Webex Link

https://unicam.webex.com/meet/massimo.callisto

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.

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.

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.