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Enterprise Data Analytics
News
Exam 2020-07-30 results: partial results are available here. Complete results will be available after project evaluation.
Exam rules update: students must confirm their presence to the next exam sessions at least 5 days before the exam date. Confirmation must be send to by mail to the teacher, esse3 registration is not sufficient.
Exam 2020-07-09 results: partial results are available here. Complete results will be available after project evaluation.
Exam 2020-06-19 results: partial results are available here. Complete results will be available after project evaluation.
Exam update: exam rules are available here. Note that exam will be done via Webex and students must have Acrobat Reader installed.
Course update: students are asked to complete the assessment questionnaire for this course.
Material update: Other materials section updated with EDA projects A.Y 2018-19.
Project update: projects and IoT dataset have been updated.
Project update: a draft of available projects is available here.
Google meet: due to some possible problems with Webex, lesson will be done via Google Meet. Instruction here. Room name edaunicam2020
.
Course start: the first lesson is planned for 12th of March 2019, only via webex room.
General Info
Teacher:
- Dr. Massimo Callisto De Donato <massimo.callistodedonato[at]gruppofilippetti.it>
ESSE3 Link
- —
Webex Link
Lessons schedule:
- 42 h - lectures, exercise sessions
- Schedule on Thursday from 14:00am to 18:00pm
- LB1 room
- Schedule (tentative)
12-mar-20 - 14:00-18:0019-mar-20 - 14:00-18:0026-mar-20 - 14:30-17:3002-apr-20 - 14:00-18:0009-apr-20 - 14:00-18:0016-apr-20 - 14:00-17:0023-apr-20 - 14:00-18:0030-apr-20 - 14:30-17:3007-mag-20 - 14:00-18:0014-mag-20 - 14:00-18:0021-mag-20 - 14:00-18:0028-mag-20 - 14:30-16:30
Students Office hours:
- Send an e-mail to the teacher to fix an appointment.
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.
Course Contents
- Acquire knowledge and competence on Big Data methodologies, techniques and technologies.
- Know most common techniques of Big Data analysis and how they apply to real world examples.
- Apply Big Data Analysis techniques into practical case studies.
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 link
- Webex doc with links
- Projects link | submitted projects
- Reference materials
- Slides course.
- Material provided by the teacher.
- Examples
- Other materials
- Projects completed on A.Y 2018-19 Description Projects