====== Technologies for Big Data Management ====== ---- ===== 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. ---- ===== 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)]] ---- ===== 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. ---- ===== 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. ---- ===== 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 * ... ---- ===== 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