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Regular version of the site
Master 2018/2019

Big Data Systems Development and Implementation

Type: Compulsory course (Big Data Systems)
Area of studies: Business Informatics
When: 1 year, 2-4 module
Mode of studies: Full time
Master’s programme: Big Data Systems
Language: English
ECTS credits: 5

Course 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

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 corporate information systems' types and their properties regarding operations with data, data necessity and impact to reaching main business goal.
  • To provide students with the knowledge of Big Data paradigm and the present the concept of Big Data approach.
  • To introduce to the students the main principles for real-time data systems and Big Data platforms.
  • To help students develop skills of designing and managing Big Data systems.
Expected Learning Outcomes

Expected Learning Outcomes

  • Student should estimate and analyze different known scientific methods and approaches in terms of data collection, storage and processing.
Course Contents

Course Contents

  • Information Technology in organizations
  • The knowledge-based view of the corporate system
  • Types of information systems
  • Big Data Platforms
  • Typical Big Data system architecture and Big Data instruments
  • Storage techniques. Databases
  • Hadoop Distributed File System
  • Hadoop essentials
  • Hadoop ecosystem
  • Architecture principles for realtime Big Data systems
  • Big Data Systems implementation
  • Management of Big Data Systems
Assessment Elements

Assessment Elements

  • non-blocking Score for the first home task
  • non-blocking Score for essay (referat)
  • non-blocking Score for the second home task
  • non-blocking Oral exam
Interim Assessment

Interim Assessment

  • Interim assessment (4 module)
    0.4 * Oral exam + 0.2 * Score for essay (referat) + 0.2 * Score for the first home task + 0.2 * Score for the second home task
Bibliography

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