Big Data & Database
Course: Geoinformatics
Structural unit: Educational and Scientific Institute "Institute of Geology"
Title
Big Data & Database
Code
ВК 2.1
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
Analyze the features of natural and anthropogenic systems and objects of the upper part of the earth's crust and its sedimentary layer. Apply knowledge to solve problems and make informed decisions in the thematic processing of geological and geospatial data. Be able to communicate with experts and experts of different levels of other fields of knowledge, including in the international context, in the global information environment. Plan and carry out scientific experiments, write scientific papers in the field of geoinformatics. Be able to carry out thematic processing and interpretation of geospatial data obtained by various methods of research of the geological environment, to develop appropriate algorithms and software products, to form geodatabases, to create web publications of cartographic data. Develop and implement mechanisms of territorial management, geoplanning, monitor regional development, draw up plans and programs.
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: A guide. - Kyiv. - 2017. - 150 p.
2. V.Pasichnyk, V.Reznichenko Orhanizatsiia baz danykh ta znan. – K.: BHV, 2006.- 383 p.
3. D.Ladychuk, V.Pichura Bazy heoinformatsiinykh danykh. – Kherson: KhDU, 2007.- 103 p.
4. Intelektualnyi analiz danykh : laboratornyi praktykum : I–navch. posibnyk / O.Iu. Vinnychuk, I.S. Vinnychuk. – Chernivtsi : Chernivetskyi nats. un-t, 2014.
Planned learning activities and teaching methods
Lectures, practical classes, consultations, self-study
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
Lecturers
This discipline is taught by the following teachers
Departments
The following departments are involved in teaching the above discipline