Advanced technologies for Big Data

Credits: 6

Semester: 3

Course: Core

Language of the course: English

Lecturer

Denis Nasonov

Objectives

Students will study the architecture of integration platforms, applications and services, the existing modern technologies of high-loaded data storage and processing systems. distinctive features of the structure of big data, the basics of the existing mechanisms for organizing their storage and management, as well as the well-known processing and analysis mechanisms, existing libraries, software and frameworks and data sources existing in the modern world.
Students will learn how to choose a suitable technology for storing and processing big data, using modern high-loaded systems for storing and processing big data, analyzing the applicability of a particular technological solution for the required tasks on existing big data, performing deployment and launching in a basic configuration of a suitable software solution for this data with further management and configuration of methods for data processing and storage.
Students will gain skills in working with software supporting the organization of storing big data and the mechanisms for their processing, assignment and allocation of resources, implementation of expert support for optimizing the work of IS, working with methods of data mining, including methods for assessing the quality of models, algorithms, methods for experimental testing of hypotheses, methods for substantiating hypotheses.

Contents

Main topics within the discipline:

  • Introduction to Specialized Technologies
  • ULB data processing platforms
  • CLAVIRE 2.0
  • ASPEN - a platform for comprehensive evaluation of streaming information processing systems
  • Expanded SparkStreaming Platform with Integrated Scheduling Engine
  • Optimize big data placement
  • Semantic Exarch repository
  • Blockchain technology in data storage tasks

Format

lectures and practical classes

Assessment

Examination.