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Regular version of the site

Big Data Systems Development and Implementation

2019/2020
Academic Year
ENG
Instruction in English
5
ECTS credits
Delivered at:
Department of Innovation and Business in Information Technologies
Course type:
Compulsory course
When:
1 year, 2-4 module

Instructors

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 Grade for module 2,3
  • non-blocking Online - test
    Examination format: The exam is taken written (multiple choice questions) with asynchronous proctoring. Asynchronous proctoring means that all the student's actions during the exam will be “watched” by the computer. The exam process is recorded and analyzed by artificial intelligence and a human (proctor). Please be careful and follow the instructions clearly! The platform: The exam is conducted on the StartExam platform. StartExam is an online platform for conducting test tasks of various levels of complexity. The link to pass the exam task will be available to the student in the RUZ. Students are required to join a session 15 minutes before the beginning. The computers must meet the following technical requirements: https://eduhseru-my.sharepoint.com/:b:/g/personal/vsukhomlinov_hse_ru/EUhZkYaRxQRLh9bSkXKptkUBjy7gGBj39W_pwqgqqNo_aA?e=fn0t9N A student is supposed to follow the requirements below: Prepare identification documents (а passport on a page with name and photo) for identification before the beginning of the examination task; Check your microphone, speakers or headphones, webcam, Internet connection (we recommend connecting your computer to the network with a cable, if possible); Prepare the necessary writing equipment, such as pens, pencils, pieces of paper, and others. Disable applications on the computer's task other than the browser that will be used to log in to the StartExam program. If one of the necessary requirements for participation in the exam cannot be met, a student is obliged to inform a professor and a manager of a program 2 weeks before the exam date to decide on the student's participation in the exams. Students are not allowed to: Turn off the video camera; Use notes, textbooks, and other educational materials; Leave the place where the exam task is taken (go beyond the camera's viewing angle); Look away from your computer screen or desktop; Use smart gadgets (smartphone, tablet, etc.) Involve outsiders for help during the exam, talk to outsiders during the examination tasks; Read tasks out loud. Students are allowed to: Write on a piece of paper, use a pen for making notes and calculations; Use a calculator; Connection failures: A short-term communication failure during the exam is considered to be the loss of a student's network connection with the StartExam platform for no longer than 1 minute. A long-term communication failure during the exam is considered to be the loss of a student's network connection with the StartExam platform for longer than 1 minute. A long-term communication failure during the exam is the basis for the decision to terminate the exam and the rating “unsatisfactory” (0 on a ten-point scale). In case of long-term communication failure in the StartExam platform during the examination task, the student must notify the teacher, record the fact of loss of connection with the platform (screenshot, a response from the Internet provider). Then contact the manager of a program with an explanatory note about the incident to decide on retaking the exam.
  • non-blocking Grade for Coursera
Interim Assessment

Interim Assessment

  • Interim assessment (4 module)
    0.4 * Grade for Coursera + 0.2 * Grade for module 2,3 + 0.4 * Online - test
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