Big Data Presentation of the course

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1 Academic year 2014/2015 Big Data Presentation of the course Prof. Riccardo Torlone Università Roma Tre

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3 A new course Second year at Roma Tre First university course on Big Data in Italy We will experiment together some technologies We will take advantage of a grant from Amazon We will know research and applicative projects on Big Data In conclusion, we will face an adventure.. 3

take advantage of a grant from Amazon We will know research and

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5 Big Data? Why? Well, because they are.. 5

6 .. BIG 6 The greater the struggle, the more glorious the triumph (The Butterfly Circus)

7 .. NECESSARY 7 It is a capital mistake to theorize before one has data (Sherlock Holmes)

8 .. CHALLENGING 8 It always seems impossible until it is done. (Nelson Mandela)

9 .. PROFITABLE 9 Data is a precious thing and will last longer than the systems themselves. (Tim Bersten Lee)

10 .. FASHIONABLE 10 I always wanted to be fashionable. (John Malkovich)

11 .. EXCITING 11 The most exciting phrase to hear in science, is not 'Eureka!' but 'That's funny... (Isaac Asimov)

12 General information Teacher Prof. Riccardo Torlone Office hours: Wednesday: 11:00-13:00 Via Vasca Navale 79 2 floor room 209 Course Web site Moodle page You must register A "social" course! Facebook: Twitter: #bigdataroma3 Lectures Monday and Thursday from 14:00 to 16:00, Room N13 Pause: Easter holidays 12

uniroma3.it/bigdata/ Moodle page http://moodle2.ing.uniroma3.it/moodle/ You must register A "social" course!

13 Goals The course aims at illustrating tools and methods for the management of big data, i.e. massive amounts of unstructured data whose size exceed the capacity of conventional database management systems to capture, store, manage and analyze. Focus on: The requirements of modern applications The problems of storing and processing big data The hardware and software solutions Strategy: Coverage of both methods and tools Exercises with real systems Practical projects Guest lectures on Big Data use cases Business seminars 13

14 Contents (provisional) Introduction Terminology, main aspects and examples of applications Big Data infrastructures Hadoop & Map-reduce; Cloud computing; NoSQL systems. Big Data processing Cleaning, transformation and data integration High level tools: Pig, Hive; New generation tools for data access. Big Data analysis Methods and algorithms for Big Data analysis; Tools for Big Data analysis: Mahout, Open R; Applications Semantic Web and Open data, Social networks, Genomic data. Business seminars 14

Big Data processing Cleaning, transformation and data integration High level tools: Pig, Hive; New generation tools for data

15 Material Books and papers Teacher slides (available on the Web side of the course) NoSQL systems: Martin J. Fowler, Pramodkumar J. Sadalage. NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence, Addison-Wesley, Scientific papers and book chapters To be published on the Web site of the course Software Hadoop Amazon Web Services Others.. 15

NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence,

16 Exams.. I have a dream.. 16

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18 Exam modalities For those attending the course: 2 projects to be done by groups of 1, 2, max 3 students Common project, deadline: mid April, weight:30% Given project, deadline: before the exam, weight:50% A written test: 30 minutes, date of the exam, weight:20% For the other students: Individual project, assigned by the teacher A written test: 3 hours Rules: Similar to all the other exams Three chances: July 2015, September 2015, February

minutes, date of the exam, weight:20% For the other students: Individual project, assigned by the teacher A

19 Main project Goals To solve a problem of Big data To experiment new technologies Steps: Find challenges and data Choose an approach to analyze data Choose suitable technologies Implement the approach Testing of the system 19

data Choose an approach to analyze data Choose suitable

20 2013/2014 course statistics Students attending the course: 52 June: Participants: 48 Average: 29,2 September: Participants: 3 Average: 28 February: Participants: 1 Average: 27 20

You should have a working knowledge of the Microsoft Windows platform. A basic knowledge of programming is helpful but not required.

You should have a working knowledge of the Microsoft Windows platform. A basic knowledge of programming is helpful but not required. What is this course about? This course is an overview of Big Data tools and technologies. It establishes a strong working knowledge of the concepts, techniques, and products associated with Big Data. Attendees