Big-Data Infrastructure and ServicesCourse code: 317211 | 8 ECTS credits
Level of Studies:Master applied studies
Year of Study:1
Goal:Enabling students to understand, apply, and develop Big data systems
Outcome:At the end of the course, students will acquire knowledge and skills that will enable them to use modern systems for storing, accessing, analyzing and researchingly structured and unstructured data collections efficiently.
Contents of the course
The storage, scalability and availability of large amounts of data.
CAP theorem, ACID vs. BASE database features.
Infrastructure of a large amount of data processing system.
Apache Hadoop storage.
Alterative Database Systems (NoSQL).
The features, advantages and disadvantages of the NoSQL database.
Database (bp) key-value type, column-oriented bp, bp oriented with graphs, bp orientated to documents, temporal bp.
Basic Concepts of Data Research. MapReduce and HPCC access to parallel and distributed data processing.
Data flow analysis, data link analysis.
Grouping of Data and Applications in Recommendation Systems.
Analysis of Social Network Graphs.
Dimensional reduction techniques.
Machine learning techniques based on large amounts of data.