didattica:ay2425:tbdm:main [Computer Science @ Unicam]

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====== Technologies for Big Data Management ======
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===== News =====
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  * <wrap em>**Exam results:**</wrap> the results of the 24 February 2025 exam are available {{https://drive.google.com/file/d/1A8VlQ0e6NyqGUxDTSGs1-R1ERu7VgXiH/view?usp=sharing| here}}.
  * <wrap em>**Exam results:**</wrap> the results of the 3 February 2025 exam are available {{https://drive.google.com/file/d/1-z8C5siZ8ZwpFSoR60HW7TwddvmvDPtV/view?usp=drive_link| here}}.
  * <wrap em>**Exam update:**</wrap> the exams scheduled for 3 February and 24 February will take place at 14:00 in room AB2.
  * <wrap em>**Projects:**</wrap> the list of the **projects** is available at following {{https://drive.google.com/drive/folders/1gFg_sGXI-29ClcwHuqW9BfHOXKHeEYhG | link}}.
  * <wrap em>**No lesson on 14 November:**</wrap> no lesson on this day.
  * <wrap em>**TBDM on Telegram**</wrap>: students can join to the Telegram group with the following {{https://t.me/+_If79QPfFR42NzQ0 | link}}.
  * <wrap em>**No lesson on 11 November:**</wrap> no lesson on this day.
  * <wrap em>**No lesson on 31 October:**</wrap> no lesson on this day.
  * <wrap em>**Webex recordings**</wrap>: recordings are available at the following [[https://docs.google.com/document/d/1JYz2CP5fzmcMjYVzYw8S4NNfHTirVYdF4AwWyJ9C14g/view | link]].
  * <wrap em>**Course start**</wrap>: the course is planned to start the **30th of September** - AB2 - Polo Lodovici A.
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===== General Info =====
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**Teacher**: 
  * [[https://didattica.unicam.it/Guide/PaginaDocente.do?docente_id=3138|Prof. Massimo Callisto De Donato]]
  * Webex room: https://unicam.webex.com/meet/massimo.callisto
  * Email: massimo.callisto[at]unicam.it

**ESSE3 Link**
  * [[|Techonologies for Big Data Management - AY 2024/25]]

**Scheduling of Lectures**:
  * Scheduling is available at the following [[:didattica:ay2425:orario_en|link]]
  
**Degrees**:
  * [[didattica:mscs|MSc in Computer Science (LM-18)]]

  
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===== Course Objectives =====

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  * 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.
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===== Syllabus =====
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  *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.
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===== Study material =====
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**Course Slides**
  * Slides {{ https://drive.google.com/drive/folders/1tcpUqLRvOnPeAJXHSAqVpLvfv6vZ1DvI?usp=sharing | link}}

  * Github {{ https://github.com/massimocallisto | link }}
  
  * Webex recordings {{ https://docs.google.com/document/d/1JYz2CP5fzmcMjYVzYw8S4NNfHTirVYdF4AwWyJ9C14g/edit?usp=sharing | link}}

  * Projects {{ https://drive.google.com/drive/folders/1gFg_sGXI-29ClcwHuqW9BfHOXKHeEYhG | link}}

  * TBDM [[http://didattica.cs.unicam.it/doku.php?id=didattica:ay2324:tbdm:main | A.A.2023/24]]

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

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===== Exams =====
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**Exam Dates A.Y. 2024/2025 (tentative)**
  * 03/02/2025
  * 24/02/2025
  * 23/06/2025
  * 07/07/2025
  * 28/07/2025
  * 08/09/2025
  * 29/09/2025
  * 02/02/2026
  * 16/02/2026

**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:
  - Project description / objectives
  - Methodology and technology being used
  - Technical implementation
  - Achieved results
  - future improvements

** Exam Results **
  * See news section

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