====== Technologies for Big Data Management ======
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===== News =====
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  * <wrap em>**Exam results 24/06/2024**</wrap>: result are available {{ https://drive.google.com/file/d/13X1_Nqc1fnnTw6YxFXVWacwqPMHRkeyg/view | here}}.
  * <wrap em>**Exam results 26/02/2024**</wrap>: result are available {{ https://drive.google.com/file/d/1PQBUeVyiWwucJPTHiPkvkFlF7xsSWxGG/view | here}}.
  * <wrap em>**Exam results 12/02/2024**</wrap>: result are available {{ https://drive.google.com/file/d/15nnudIibYYmleNuQLaVBybW46BTjUo94/view | here}}.
  * <wrap em>**Exam results 01/02/2024**</wrap>: result are available {{ https://drive.google.com/file/d/1r_oiqU6QVW56GVF6QGIEy2wrwffmBcSO/view | here}}.
  * <wrap em>**Exam update, 1st of February - 14:00:**</wrap>: exam is planned in AB1.
  * <wrap em>**Course completed**</wrap>: 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.
  * <wrap em>**No lesson the 11th of December**</wrap>: no lesson on this day.
  * <wrap em>**Projects**</wrap>: the list of the project is available at the following {{https://drive.google.com/drive/folders/1u0BUKeyhf7tLIE9KKdDPeTubxrloqW5j | link}}.
  * <wrap em>**No lesson the 30th of October**</wrap>: no lesson on this day.
  * <wrap em>**No lesson the 23th of October**</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>**Course delayed**</wrap>: the course is planned to start the **9th of October** - LB1.
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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 2023/24]]

**Scheduling of Lectures**:
  * Scheduling is available at the following [[:didattica:ay2324: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/1VH3KWCiE7uqrTFA_dQFJAwxQIqUGR1Va?usp=sharing | link}}

  * Github {{ https://github.com/massimocallisto | link }}
  
  * Webex recordings {{ https://docs.google.com/document/d/1MGHV2vtRe9-9wFq63DVWC68X1GCqMEI4AvP_9l-rAXM/edit?usp=sharing | link}}

  * Projects {{ https://drive.google.com/drive/folders/1u0BUKeyhf7tLIE9KKdDPeTubxrloqW5j | link }}

  * TBDM [[http://didattica.cs.unicam.it/doku.php?id=didattica:ay2223:tbdm:main | A.A.2022/23]]

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

** Exam Results **
  * See news section

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