Big Data & Database
Course: Geoinformation systems and Technologies
Structural unit: Educational and Scientific Institute "Institute of Geology"
            Title
        
        
             Big Data & Database
        
    
            Code
        
        
            ВБ 2.02
        
    
            Module type 
        
        
            Вибіркова дисципліна для ОП
        
    
            Educational cycle
        
        
            Second
        
    
            Year of study when the component is delivered
        
        
            2023/2024
        
    
            Semester/trimester when the component is delivered
        
        
            3 Semester
        
    
            Number of ECTS credits allocated
        
        
            4
        
    
            Learning outcomes
        
        
            - Know the methods of collecting and structuring information for research in the field of geoinformatics, photogrammetry and remote sensing, methods of digital image processing in special packages, programs and GIS.
- Process the results of geodetic measurements, topographic and cadastral surveys, using geographic information technologies and computer software and database management systems.
- Have modern technologies for data collection, processing, exchange, transformation and integration in various fields of geosciences.
        
    
            Form of study
        
        
            Full-time form
        
    
            Prerequisites and co-requisites
        
        
            1. Successful mastering of at least one course in database management or development, basics of large data sets.
2. Have skills in programming, working with spreadsheets, databases and other data sources.
        
    
            Course content
        
        
            There is an acquaintance with the basics of designing data mining systems, methods of working with big data, building specific database structures (data warehouses, data showcases). The general paradigms of data science, their connection with the design of databases, their place in modern systems of decision support and data analysis are studied. Students acquire practical skills of intellectual analysis of attributive information.
        
    
            Recommended or required reading and other learning resources/tools
        
        
            1. Marchenko O.O., Rossada T.V. Actual problems of Data Mining: Navch. posib. - Kyiv. — 2017.
2. Pasichnyk, V., Reznichenko V.  Orhanizatsiia baz danykh ta znan. – K.: BHV, 2006.
3. Ladychuk D., Pichura V. Bazy heoinformatsiinykh danykh. – Kherson: KhDU, 2007.
4. Intelligent data analysis: laboratory practice: I-studies. manual / O.Iu. Vinnychuk, I.S. Vinnychuk. – Chernivtsi : Chernivetskyi nats. un-t, 2014.
        
    
            Planned learning activities and teaching methods
        
        
            Lectures, practical classes, independent work
        
    
            Assessment methods and criteria
        
        
            The control is carried out according to the modular rating system and includes: implementation of 2 semester practical projects (where students must demonstrate the quality of acquired knowledge and solve problems using the methods and tools outlined by the teacher), implementation of 10 independent practical works (where students must demonstrate the quality of acquired knowledge and solve tasks without limitation of tools and techniques for solving the problem) and conducting 2 written modular tests. The final assessment is conducted in the form of a written exam.
        
    
            Language of instruction
        
        
            ukrainian
        
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