Master 2022/2023

Research Seminar

Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'

Category 'Best Course for New Knowledge and Skills'

Type: Compulsory course (Business Analytics and Big Data Systems)

Area of studies: Business Informatics

Delivered by: Department of Business Informatics

Where: Graduate School of Business

When: 2 year, 1-3 module

Mode of studies: offline

Open to: students of one campus

Instructors: Armen Beklaryan, Emin Erkan Korkmaz

Master’s programme: Business Analytics and Big Data Systems

Language: English

ECTS credits: 6

Contact hours: 48

Course Syllabus

Abstract

This course's key objective is to make the students familiar with implementing the most important big data concepts in various business domains. We will discuss industries like: Banking and Securities; Communications, Media and Entertainment; Healthcare; Education; Manufacturing and Natural Resources; Government; Insurance; Retail and Wholesale trade

Learning Objectives

• This course gives insights into how big data technologies impact the business

Expected Learning Outcomes

• Describe the ethics, governance, and sustainability challenges relating to Big Data
• Design and evaluate an approach for the architecture of infrastructure for Big Data products based upon particular needs, including selecting an appropriate set of technologies, and governance strategy for storage and processing data
• Discuss the impact of digitization and the adoption of Big Data in business and overall society
• Explain the challenges of creating and maintaining Big Data products

Course Contents

• Big Data Ecosystem
• (Big) Data Management
• Data Products and Economics
• Data Culture and Ethics

Assessment Elements

• Activity during classes
• Project defense
• State-of-the-art
• Exam

Interim Assessment

• 2022/2023 3rd module
  0.35 * Exam + 0.15 * Activity during classes + 0.25 * State-of-the-art + 0.25 * Project defense

Bibliography

Recommended Core Bibliography

• Malaska, T., & Seidman, J. (2018). Foundations for Architecting Data Solutions : Managing Successful Data Projects: Vol. First edition. O’Reilly Media.
• Thomas Erl, Wajid Khattak, & Paul Buhler. (2016). Big Data Fundamentals : Concepts, Drivers & Techniques. Prentice Hall.

Recommended Additional Bibliography

• Jules S. Damji, Brooke Wenig, Tathagata Das, & Denny Lee. (2020). Learning Spark. O’Reilly Media.
• Kleppmann, M. (2017). Designing Data-Intensive Applications : The Big Ideas Behind Reliable, Scalable, and Maintainable Systems. Sebastopol, CA: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1487643
• Mark Richards, & Neal Ford. (2019). Fundamentals of Software Architecture : An Engineering Approach. O’Reilly Media.

Authors

• BEKLARYAN ARMEN LEVONOVICH