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didattica:ay2425:tbdm:main [2024/09/24 09:06] – created - external edit 127.0.0.1 | didattica:ay2425:tbdm:main [2024/09/25 13:40] (current) – [Study material] massimo | ||
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- | ====== | + | ====== |
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===== News ===== | ===== News ===== | ||
<WRAP center round important 95%> | <WRAP center round important 95%> | ||
- | There is not any news. | + | * <wrap em> |
</ | </ | ||
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<WRAP box round 95% center> | <WRAP box round 95% center> | ||
**Teacher**: | **Teacher**: | ||
- | * [[https://computerscience.unicam.it/massimo-callisto-de-donato|Prof. Massimo Callisto De Donato]] | + | * [[https://didattica.unicam.it/Guide/ |
+ | * Webex room: https:// | ||
+ | * Email: massimo.callisto[at]unicam.it | ||
**ESSE3 Link** | **ESSE3 Link** | ||
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</ | </ | ||
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+ | |||
+ | ===== Course Objectives ===== | ||
+ | |||
+ | <WRAP box round 95% center> | ||
+ | * 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, | ||
+ | * Knowledge of the main Big Data technological frameworks and application in real case studies. | ||
+ | * Highlight some Intelligent Data Analysis techniques. | ||
+ | </ | ||
+ | |||
+ | ---- | ||
+ | |||
+ | ===== Syllabus ===== | ||
+ | <WRAP round 95% center box> | ||
+ | *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, | ||
+ | *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 ===== | ||
+ | <WRAP box round center 95%> | ||
+ | **Course Slides** | ||
+ | * Slides {{ https:// | ||
+ | |||
+ | * Github {{ https:// | ||
+ | | ||
+ | * Webex recordings {{ https:// | ||
+ | |||
+ | * Projects (TBD) | ||
+ | |||
+ | * TBDM [[http:// | ||
+ | |||
+ | * **Reference materials** | ||
+ | * Slides course. | ||
+ | * Material provided by the teacher. | ||
+ | * Examples | ||
+ | * ... | ||
+ | * Other materials | ||
+ | * ... | ||
+ | |||
+ | </ | ||
+ | ---- | ||
+ | |||
+ | ===== Exams ===== | ||
+ | <WRAP box round center 95%> | ||
+ | **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, | ||
+ | - Project description / objectives | ||
+ | - Methodology and technology being used | ||
+ | - Technical implementation | ||
+ | - Achieved results | ||
+ | - future improvements | ||
+ | |||
+ | ** Exam Results ** | ||
+ | * See news section | ||
+ | |||
+ | </ | ||
+ | |||