====== Technologies for Big Data Management ======
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===== News =====
* **Exam results 09/09/2024**: result are available {{ https://drive.google.com/file/d/1cZRhsrU6g2Raz-Hibj58-WgQNerdfV-Y/view | here}}.
* **Exam update, 09/09/2024:**: exam is planned at 15:00 in AB2
* **Exam results 08/07/2024**: result are available {{ https://drive.google.com/file/d/1eTNoZZunokaTELTJE30tlQSySOXul_bR/view | here}}.
* **Exam results 24/06/2024**: result are available {{ https://drive.google.com/file/d/13X1_Nqc1fnnTw6YxFXVWacwqPMHRkeyg/view | here}}.
* **Exam results 26/02/2024**: result are available {{ https://drive.google.com/file/d/1PQBUeVyiWwucJPTHiPkvkFlF7xsSWxGG/view | here}}.
* **Exam results 12/02/2024**: result are available {{ https://drive.google.com/file/d/15nnudIibYYmleNuQLaVBybW46BTjUo94/view | here}}.
* **Exam results 01/02/2024**: result are available {{ https://drive.google.com/file/d/1r_oiqU6QVW56GVF6QGIEy2wrwffmBcSO/view | here}}.
* **Exam update, 1st of February - 14:00:**: exam is planned in AB1.
* **Course completed**: 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.
* **No lesson the 11th of December**: no lesson on this day.
* **Projects**: the list of the project is available at the following {{https://drive.google.com/drive/folders/1u0BUKeyhf7tLIE9KKdDPeTubxrloqW5j | link}}.
* **No lesson the 30th of October**: no lesson on this day.
* **No lesson the 23th of October**: no lesson on this day.
* **TBDM on Telegram**: students can join to the Telegram group with the following {{https://t.me/+_If79QPfFR42NzQ0 | link}}.
* **Course delayed**: the course is planned to start the **9th of October** - LB1.
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===== General Info =====
**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 =====
* 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 =====
*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 =====
**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 =====
**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