Big Data Analytics
News
- Exam results 2017-11-30: results have been published link . Students can confirm their vote by mail and register at the next exam session.
- Papers 2016-17: available here.
- Exam results 2017-09-21: results have been published link . Students can confirm their vote by mail and register at the next exam session.
- Exam results 2017-07-13: results have been published link . Students can confirm their vote by mail and register at the next exam session.
- Exam update: The exam fixed on 13th July will be in AB2 - Polo Ludovici.
- Exam results 2017-06-22: results have been published link . Students can confirm their vote by mail and register at the next exam session of 2017-07-13.
- Exam results 2017-03-30: results have been published link . Students can confirm vote by mail.
- For further informaionon about the exam: I could be be available on saturday morning at Campus - Giurisprudenza building (aula 1, piano terra). For who is interested, please send me an email in order to schedule an appointment.
- Exam results 2017-03-16: results have been published link . Students can register their vote at the end of the next exam session of 2017-03-30.
- For students that need information or have questions: I could be be available on saturday morning at Campus - Giurisprudenza building (aula 1, piano terra). For who is interested, please send me an email in order to schedule an appointment.
- Exam update: The exam fixed on 16th March will be in AB3 - Polo Ludovici.
- No lesson 9th february 2016: Lecture suspended. Next lecture is 16th february 2016 15:00pm to 19:00pm. Slides of the suspended lesson have been uploaded.
- Course start: lectures will start on 15th December at Polo Ludovici from 15:00pm to 18:00pm AB2 room.
- Course stop: lectures suspended due to earthquake.
- New lecture room: next lectures will be held in room E. W. Dijkstra.
- Course start: lessons will start on 6th October 2016.
General Info
Teacher:
- Dr. Massimo Callisto De Donato <massimo.callistodedonato[at]gruppofilippetti.it>
Lessons schedule:
- 42 h - lecture and exercise sessions
- Thursday: 15:00 pm – 18:00 pm
Students Office hours:
- Send an e-mail to the teacher to fix an appointment.
Course Objectives
- The course gives an introduction to the Big Data models and related techniques required to perform data analysis in real world examples.
- The course focuses on data with “Big Data characteristics” such as data that can generated by any kind of systems with an high volume, data that grows very fast, data highly semi-structured or un-structured.
- The course highlights the correlations between Big Data and related fields of IoT and Smart Cities.
- The course introduces all relevant state-of-the-art concepts, methods and technologies enabling Big Data Analysis in real world business cases.
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 Big Data
- What are Big Data
- Big Data in the real world
- Needs and Challenges of Big Data
- Characterize Big Data
- Big Data models: from storage to processing
- The V model
- From datawarehouse to Big Data
- Aspect of Distributing Storage
- Distributed Processing
- NoSQL
- Distributed Search
- Big Data Analysis: Methodologies and Techniques
- How enabling Big Data Processing
- The Hadoop framework
- HDFS: hadoop filesystem
- Computational framework: MapReduce and YARN
- HBase as NoSQL database
- Other related hadoop processing frameworks
- Practical Examples
- Apache Spark
- Apache Cassandra
- Batch processing Vs RealTime processing
- Apache Spark Streaming
- Apache Storm
- Big Data Analysis applications
- Big Data in practice: connecting with IoT
- Use cases scenario
- Advance Big Data Analysis
- Distribuited graph modelling framework
- Machine Learning
- Baysian Newtork
Study material
Course Slides
- slide 1st_0 lesson slides_1
- slide 1st_1 lesson slides_1_1
- slide 2st_1 lesson slides_2_1
- slide 2st_2 lesson slides_2_2
- slide 2st_3 lesson slides_2_3
- slide 3st_1 lesson slides_3
- slide 4st_1 lesson slides_4
- slide 4st_2 lesson slides_4_2
- slide 5st_1 lesson slide 5_1
- slide 5st_2 lesson slide 5_2
- slide 6st_1 lesson slide 6_1
- slide 7st_1 lesson slide 7_1
- slide 8st_1 lesson slide 8_1
- slide 9st_1 lesson slide 9_1
- slide 10st_1 lesson slide 10_1
- slide 11st_1 lesson slide 11_1
- Reference materials
- Slides course.
- Material provided by the teacher.
- Homework
Exams
Exam Dates A.Y. 2015/2016
- 16/03/2017 - 15:00
- 30/03/2017 - 15:00
- 22/06/2017 - 15:00
- 13/07/2017 - 15:00
- 21/09/2017 - 15:00
- 01/02/2018 - 15:00
- 22/02/2018 - 15:00
Exam rules:
- Writing Examination on the topics of the course
- Open or multiple-choice questions + Exercise
- 2 h
- Homework assignment evaluation
Exam Results
