Big Data Systems Development and Implementation

Master 2020/2021

Type: Elective course

Area of studies: Business Informatics

Delivered by: Department of Business Informatics

Where: Graduate School of Business

When: 1 year, 3, 4 module

Mode of studies: offline

Instructors: Petr Baranov, Сулейкин Александр Сергеевич

Master’s programme: Big Data Systems

Language: English

ECTS credits: 5

Contact hours: 40

Full Syllabus

Abstract

Big data Systems address needs for structured and unstructured data across a wide spectrum of domains such as Web, social networks, enterprise, cloud, mobile, sensor networks, multimedia/streaming, and cyber physical and high performance systems. The course is focused on the relevant architecture of Big Data Systems, their building, implementation and management. The course emphasizes the skills and knowledge to identify and communicate business system needs, to develop right Big Data system architecture and software/hardware infrastructure and implement it into organizations to improve business performance and get profit from available data. The course contains an overview and case studies of contemporary Big Data systems and highlights the areas of greatest potential application of the technology.

Learning Objectives

To teach students to understand the connections between organization's business goals and data possessed by the organization.
To present the variety of modern Open-Source Big Data applications and platforms
To get hands-on experience with Big Data processing, storage and vasualization tools
To provide students with the knowledge of Big Data paradigm and data-driven approach
To introduce to the students the need and Architectural Overview of modern DWH, Data Lake and Data Mesh
To help students develop skills for designing and managing data pipelines in organizations

Expected Learning Outcomes

Student should estimate and analyze different known scientific methods and approaches in terms of data collection, storage and processing
Student should be capable to make managerial decisions, to assess their consequences and to bear responsibility for the outcomes
These indicated and contributed during the preparation of explanation and analysis of the particular area for data collection, storage and processing, particular market and business-model
Students should identify and make prognoses about modern approaches on increasing business efficiency
Students should identify and chose optimal solutions for improving it-infrastructure and business architecture of the company after implementation relevant big data collection, storage and processing processes
Public presentation of the proposed and developed methods, approaches and architectures during the course time and analytical essay (referat) will indicate the level of efficiency of the students work

Course Contents

Analytical platforms evolution
Batch and Streaming data processing
DWH, Data Lake and Data Mesh
Big Data Processing Engines
Big Data Platforms
Typical Big Data system architecture and Big Data instruments
SQL and NoSQL Databases for Big Data Projects
Hadoop Distributed File System
Hadoop essentials
Hadoop ecosystem
Message Oriented Systems
Cluster Multitenancy
Big Data Systems implementation in different domains
Management of Big Data Systems

Assessment Elements

Exam
Class work & attendance
Big Data Service presentation
Group Project Presentation: Small Big Data

Interim Assessment

Interim assessment (4 module)
0.2 * Big Data Service presentation + 0.1 * Class work & attendance + 0.3 * Exam + 0.4 * Group Project Presentation: Small Big Data

Bibliography

Recommended Core Bibliography

Ali, A., Qadir, J., Rasool, R. ur, Sathiaseelan, A., & Zwitter, A. (2016). Big Data For Development: Applications and Techniques. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsarx&AN=edsarx.1602.07810

Recommended Additional Bibliography

Adams, T. (2015). Development of a Big Data Framework for Connectomic Research. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsarx&AN=edsarx.1501.06102
Duque-Jaramillo, J. C., & Villa-Enciso, E. M. (2016). Big Data: development, advancement and implementation organizations in information age ; Big Data: desarrollo, avance y aplicación en las organizaciones de la era de la información. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.A8867B75

Course Syllabus