Introduction to Big Data

Entry requirements: basic programming skills, basic SQL\DBMS knowledge

Credits: 5

Course: Elective

Language of the course: English

Objectives

  • Study of the main reasons of Big Data formation. It’s detection and identification.
  • Introduction to Grid technologies, WMS, MapReduce, stream data processing
  • Understanding of MapReduce principles and Apache Hadoop technology
  • Understanding of HDFS principles and building of Apache Hadoop infrastructure
  • Introducing to Apache Storm Technology

 

Contents

Today Big Data is one of key aspect in the field of behavior analysis and modeling of many social and economic effects in various fields of science. This is a strong incentive to learn this course, which will give a brief description of the Big Data history formation, the definition and identification of Big Data areas. After this the basics of HDFS file system will be discussed, as well as Apache Hadoop technology will be overviewed, which is built on top of HDFS, with integrated MapReduce paradigm. Also Apache Storm technology will be assimilated through the practically performing tasks of large data processing in a stream mode. On completion of the course, the students will obtain basic skills in Big Data technologies, such as, Apache Hadoop and Apache Storm.

Format

Lectures and workshops

Assessment

Attendance is mandatory.

Grading: 60% course work: 20% data crawler, 20% implementation on Big Data technologies, 20% data analysis and reporting; 20% work in workshops; 20% final examination test.