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Магистратура 2021/2022

Научно-исследовательский семинар по системам больших данных "Большие Данные: принципы и парадигмы"

Направление: 38.04.05. Бизнес-информатика
Когда читается: 1-й курс, 1 модуль
Формат изучения: без онлайн-курса
Охват аудитории: для своего кампуса
Прогр. обучения: Бизнес-аналитика и системы больших данных
Язык: английский
Кредиты: 3
Контактные часы: 28

Course Syllabus

Abstract

Research seminar Big Data: Principles and Paradigms captures the state-of-the-art research on the architectural aspects, technologies, and applications of Big Data. We will learn about Big Data trends and challenges, Data Management and Governance, Data Science, and Data Analytics. Course discusses potential future directions and technologies that facilitate insight into numerous scientific, business, and consumer applications
Learning Objectives

Learning Objectives

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

Expected Learning Outcomes

  • Define Big data issues and challenges
  • Define Big data issues and challenges
  • Define the approach to managing the flow of an information system's data throughout its life cycle
  • Describe the ethics, and privacy challenges relating to Big Data
  • Design and evaluate an approach for the architecture of infrastructure for Big Data products
  • Discuss the new data intensive techniques and mathematical models to build data analytics
  • Identify and understand the key factors and mechanisms involved in the diffusion and utilization of big data
Course Contents

Course Contents

  • Big Data's Big Potential
  • Big Data's Big Problems
  • Principles underlying Big Data computing
  • Computational platforms supporting Big Data applications
  • Life-cycle data management
  • Data analysis algorithms
  • Big Data privacy and ethical issues
  • Challenges in Big Data management and analytics
Assessment Elements

Assessment Elements

  • non-blocking Activity during classes
  • non-blocking Exam
Interim Assessment

Interim Assessment

  • 2021/2022 1st module
    0.5 * Activity during classes + 0.5 * Exam
Bibliography

Bibliography

Recommended Core Bibliography

  • Buyya, R., Calheiros, R. N., & Vahid Dastjerdi, A. (2016). Big Data : Principles and Paradigms. Cambridge, MA: Morgan Kaufmann. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1145031
  • Raheem, N. (2019). Big Data : A Tutorial-Based Approach (Vol. First edition). Boca Raton: Chapman and Hall/CRC. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2031482

Recommended Additional Bibliography

  • Ogrean Claudia. (2018). Relevance of Big Data for Business and Management. Exploratory Insights (Part I). https://doi.org/10.2478/sbe-2018-0027
  • Ogrean Claudia. (2019). Relevance of Big Data for Business and Management. Exploratory Insights (Part II). https://doi.org/10.2478/sbe-2019-0013
  • Prabhu, C. S. R. (2019). Fog Computing, Deep Learning and Big Data Analytics-Research Directions. Singapore: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1994845
  • Soares, S. (2012). Big Data Governance : An Emerging Imperative: Vol. 1st ed. MC Press.

Authors

  • PANFILOV PETR BORISOVICH