Introduction to Big Data
- The course is to introduce students to the core concepts of Big Data analysis and application to selected applied fields
- - Know the fundamental concepts, principles and approaches to description of the Big Data Landscape. - Be able to understand the main problems of the Big Data Analysis, get acquainted to the architectural components and programming models used for scalable data analysis. - Learn how to use one of the most common frameworks, Hadoop.
- The following competences: - Being able to explicate the scientific essence of problems in the professional field - Being able to use the relevant mathematical and technical tools for processing, analysis and systematization of data on the topic of research - Being able to prepare scientific reports and presentations
- 1. ON-LINE PHASE- Introduction. - Big Data: Why and Where. - Characteristics of Big Data and Dimensions of Scalability. - Data Science: Getting Value out of Big Data. - Foundation for Big Data Systems and Programming. - Systems: Getting Started with Hadoop
- 2. OFF-LINE PHASESelected topics related to Big Data in: - Social Network Analysis - Industrial Internet - Healthcare
- 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
- Hillyard, S., & Hand, M. (2014). Big Data? : Qualitative Approaches to Digital Research (Vol. First edition). Bingley, UK: Emerald Group Publishing Limited. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=908919