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Магистратура 2019/2020

Научно-исследовательский семинар

Статус: Курс обязательный (Системы больших данных)
Направление: 38.04.05. Бизнес-информатика
Когда читается: 1-й курс, 1-4 модуль
Формат изучения: Full time
Прогр. обучения: Системы больших данных
Язык: английский
Кредиты: 10

Программа дисциплины

Аннотация

The objective of the Research seminar is to elaborate skills and experience in development work in the process of students’ preparation for theses and graduate qualification papers (master’s thesis) of the master’s program “Big Data Systems”. The course focuses on the research of the areas of technologies and big data appliance, study of the practical work with instrumentation of Big Data, as well as the analysis of the development of technologies. The main purpose of the Research seminar is to develop academic competences in analysis and evaluation of the impact of new information technologies, including Big Data and related technologies on business performance and its architecture, as well as best practices of the Big Data technologies. The final goal of the Seminar is to make student's scientific activities being permanent and systematic element of the educational process, to include students into the life of typical scientists, to help learning methodology, technology and tools for research activity.
Цель освоения дисциплины

Цель освоения дисциплины

  • Training students skills in an academic work, including preparation and carrying out scientific projects, writing scientific papers
  • Training scientific discussion and presentation of ideas, concepts, research results, projects and research papers
  • Training the use of Big Data technologies for scientific activities
  • Training methods and skills in scientific forecasting for definition of technological trends in the field of information technologies
Результаты освоения дисциплины

Результаты освоения дисциплины

  • Uses big data technology to address the challenges of building an organization's information infrastructure
  • Uses architectural solutions based on big data
  • Assesses the cost-effectiveness of big data management solutions
  • Understands and evaluates the prospects for the development of functionality and applications of Big Data technologies
Содержание учебной дисциплины

Содержание учебной дисциплины

  • Mathematical and technological basis of big data tooling
    The research into the peculiarities of appliance technologies to the tasks, connected with the formation of information infrastructure of an organization, new opportunities for analytics and decision-taking
  • Architectural solutions on the basis of big data for enterprises
    The transformation of the system of data managing, formation of information assets of an enterprise, systems of data collection about business processes, elaboration of external data, new design of cooperation, system interaction
  • Big data economics
    The evaluation of economic efficiency of solutions for enterprise management on the basis of big data technologies, possibilities to use information assets of enterprises, opportunities to use solutions on the basis of unstructured information from various sources in the enterprise administration
  • Prospects for the development of functionality and spheres of Big Data technology appliance
Элементы контроля

Элементы контроля

  • неблокирующий Created with Sketch. Classroom work
  • неблокирующий Created with Sketch. Individual Work (self-study)
  • неблокирующий Created with Sketch. Exam1
  • неблокирующий Created with Sketch. Exam2
  • неблокирующий Created with Sketch. Project
Промежуточная аттестация

Промежуточная аттестация

  • Промежуточная аттестация (2 модуль)
    0.5 * Classroom work + 0.3 * Exam1 + 0.2 * Individual Work (self-study)
  • Промежуточная аттестация (4 модуль)
    0.5 * Classroom work + 0.2 * Exam2 + 0.3 * Project
Список литературы

Список литературы

Рекомендуемая основная литература

  • Berman, J. J. (2018). Principles and Practice of Big Data : Preparing, Sharing, and Analyzing Complex Information (Vol. Second Edition). London: Academic Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1731816
  • Big data in economics: evolution or revolution? (2017). United Kingdom, Europe: Cambridge University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.5BD0A2C5
  • 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
  • Liu, S., Xie, Y., Ge, Z., & McGree, J. (2016). Computational and Statistical Methods for Analysing Big Data with Applications. London: Academic Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1102854
  • Mihai Andronie, Daniel Adrian Gârdan, Ionel Dumitru, Iuliana Petronela Gârdan, Irina Elena Andronie, & Cristian Uță. (2019). Integrating the Principles of Green Marketing by Using Big Data. Good Practices. Amfiteatru Economic, (50), 258. https://doi.org/10.24818/EA/2019/50/258