Innovation in Data Analysis (курсова робота)

Major: System Analysis
Code of subject: 6.124.03.E.114
Credits: 2.00
Department: Information Systems and Networks
Lecturer: Dr.Tech.Sc., Professor, Andrii Berko
Semester: 8 семестр
Mode of study: денна
Learning outcomes: • Knowledge and understanding of the scientific basis for the creation of information technology for data analysis, their capabilities and areas of use, ways to improve them; • ability to form theoretical and practical justifications for the use of certain information technology in specific tasks; • skills for practical application of knowledge of the current state of Affairs and the latest information technologies in the field of data analysis; • gaining of teamwork and conflict resolution skills; • the ability to analyze practical situations for the effective use of information technology of data analysis, its replacement or complement.
Required prior and related subjects: • Specialized programming languages • Non-Relational databases • Technologies of machine learning
Summary of the subject: 1. The concept of innovation. Types of innovations. Classification of innovations. 2. Data analysis innovations. 3. Stages of creation of innovative it data analysis. 4. Defining the vision and purpose of innovation. 5. Formulation of innovation goals. 6. Justification of data analysis innovation. 7. Evaluating the effects of data analysis innovation. 8. The development of strategy for development innovation analysis of the data. 9. Identify the requirements, limitations, and risks of creating and analyzing data. 10. The calculation of resources, the innovation of the data analysis. 11. Planning the creation and analysis of data. 12. Modeling of data analysis innovation domain processes 13. Modeling of domain objects for data analysis. 14. Implementation of the data creation and analysis plan 15. Development of a prototype for innovation data analysis 16. Implementation of data analysis innovation.
Assessment methods and criteria: • Current control (45%): written reports on laboratory work, oral examination; • Final control (55% of exam): in written, verbally.
Recommended books: 1. A Guide to the Project Management Body of Knowledge (PMBOK® Guide) – Fifth Edition, Project Management Institute, Inc., 2013 2. Karl E. Wiegers, Software Requirements Second Edition, Mcrosoft Press, 2004 3. Жежнич П. І. Технології інформаційного менеджменту : навч. посіб. / П. І. Жежнич. – Л. : Вид-во Львів. політехніки, 2010. – 260 с. 4. Палеха Ю.І., Горбань Ю.І. Інформаційний бізнес : підручник / Ю.І. Палеха, Ю.І. Горбань — К.: Вид-во Ліра-К. 2015.- 492 с. 5. Палеха Ю.І., Палеха О.Ю. Маркетинг інформаційних продуктів і послуг : навч. посіб. / Ю.І. Палеха, О.Ю. Палеха. К. : Вид-во Ліра-К: 2013. – 478 с.

Innovation in Data Analysis

Major: System Analysis
Code of subject: 6.124.03.E.112
Credits: 6.00
Department: Information Systems and Networks
Lecturer: Dr.Tech.Sc., Professor, Andrii Berko
Semester: 8 семестр
Mode of study: денна
Learning outcomes: • Knowledge and understanding of the scientific basis for the creation of information technology for data analysis, their capabilities and areas of use, ways to improve them; • ability to form theoretical and practical justifications for the use of certain information technology in specific tasks; • skills for practical application of knowledge of the current state of Affairs and the latest information technologies in the field of data analysis; • gaining of teamwork and conflict resolution skills; • the ability to analyze practical situations for the effective use of information technology of data analysis, its replacement or complement.
Required prior and related subjects: • Specialized programming languages • Non-Relational databases • Technologies of machine learning
Summary of the subject: 1. The concept of innovation. Types of innovations. Classification of innovations. 2. Data analysis innovations. 3. Stages of creation of innovative it data analysis. 4. Defining the vision and purpose of innovation. 5. Formulation of innovation goals. 6. Justification of data analysis innovation. 7. Evaluating the effects of data analysis innovation. 8. The development of strategy for development innovation analysis of the data. 9. Identify the requirements, limitations, and risks of creating and analyzing data. 10. The calculation of resources, the innovation of the data analysis. 11. Planning the creation and analysis of data. 12. Modeling of data analysis innovation domain processes 13. Modeling of domain objects for data analysis. 14. Implementation of the data creation and analysis plan 15. Development of a prototype for innovation data analysis 16. Implementation of data analysis innovation.
Assessment methods and criteria: • Current control (45%): written reports on laboratory work, oral examination; • Final control (55% of exam): in written, verbally.
Recommended books: 1. A Guide to the Project Management Body of Knowledge (PMBOK® Guide) – Fifth Edition, Project Management Institute, Inc., 2013 2. Karl E. Wiegers, Software Requirements Second Edition, Mcrosoft Press, 2004 3. Жежнич П. І. Технології інформаційного менеджменту : навч. посіб. / П. І. Жежнич. – Л. : Вид-во Львів. політехніки, 2010. – 260 с. 4. Палеха Ю.І., Горбань Ю.І. Інформаційний бізнес : підручник / Ю.І. Палеха, Ю.І. Горбань — К.: Вид-во Ліра-К. 2015.- 492 с. 5. Палеха Ю.І., Палеха О.Ю. Маркетинг інформаційних продуктів і послуг : навч. посіб. / Ю.І. Палеха, О.Ю. Палеха. К. : Вид-во Ліра-К: 2013. – 478 с.