Information processing and analysis technologies
Course: Applied mathematics
Structural unit: Faculty of Computer Science and Cybernetics
            Title
        
        
            Information processing and analysis technologies
        
    
            Code
        
        
            Module type 
        
        
            Вибіркова дисципліна для ОП
        
    
            Educational cycle
        
        
            Second
        
    
            Year of study when the component is delivered
        
        
            2021/2022
        
    
            Semester/trimester when the component is delivered
        
        
            4 Semester
        
    
            Number of ECTS credits allocated
        
        
            4
        
    
            Learning outcomes
        
        
            PLO3. Gaining knowledge for the ability to evaluate existing technologies and on the basis of analysis to form requirements for the development of advanced information technologies.
PLO6. Ability to design and use existing data integration tools, process data stored in different systems.
PLO7. Ability to organize, configure and develop Web-systems using the principles of distributed systems, hypertext systems, relevant hardware and software.
PLO10. Ability to build models of physical and production processes, design storage and data space, knowledge base, using charting techniques and standards for information systems development.
        
    
            Form of study
        
        
            Distance form
        
    
            Prerequisites and co-requisites
        
        
            1. Know: the basics of tabular data manipulation, the concept of relational databases and their transformations, in particular, normalization and denormalization.
2. To be able: to apply in practice tool environments of programming and data processing.
3. Have the skills: visual design.
        
    
            Course content
        
        
            The purpose of the discipline - the acquisition of basic knowledge and skills of data processing technologies and development of information and analytical systems.
As a result of studying the discipline the student must:
know the basic concepts of OLAP-technology for working with databases, development of data warehouses, OLAP-modeling cubes;
be able to apply in practice tool environments in the design and development of analytical integrated interactive reports and panels (dashboards), create and export pivot analytical tables.
        
    
            Recommended or required reading and other learning resources/tools
        
        
            1.	Leskovec J. Mining of Massive Datasets  / Jure Leskovec Anand Rajaraman, Jeffrey David Ullman // Stanford Univ.  – 2010.
4.	Understanding Microsoft OLAP Architecture https://docs.microsoft.com/en-us/analysis-services/multidimensional-models/olap-physical/understanding-microsoft-olap-architecture.
        
    
            Planned learning activities and teaching methods
        
        
            Lectures, laboratory classes, independent work, tests, defense of laboratory work, exam.
        
    
            Assessment methods and criteria
        
        
            - Semester assessment:
1. Protection of laboratory works: LO 2.1 –– 30/18 points.
2. Protection of laboratory works: LO 2.2 –– –– 30/18 points.
Final assessment (in the form of an exam):
- maximum number of points: 40 points;
- learning outcomes which shall be assessed: LO1.1, LO1.2.
        
    
            Language of instruction
        
        
            Ukrainian
        
    Lecturers
This discipline is taught by the following teachers
                    Volodymyr
                    F.
                    Kuzenko
                
                
                    Theory and Technology of Programming 
Faculty of Computer Science and Cybernetics
            Faculty of Computer Science and Cybernetics
Departments
The following departments are involved in teaching the above discipline
                        Theory and Technology of Programming
                    
                    
                        Faculty of Computer Science and Cybernetics