Analytical Data Warehouse

Major: System Analysis
Code of subject: 6.124.01.E.086
Credits: 5.00
Department: Information Systems and Networks
Lecturer: Ph.D. Mykich Khrystyna Ihorivna
Semester: 7 семестр
Mode of study: денна
Learning outcomes: models and methods of designing and implementing data warehousing; decisions on technology data warehousing; the practical application of basic methods, tools and techniques of modern storage.
Required prior and related subjects: Databases and knowledge bases organization
Summary of the subject: The concept of data hypercube and its relationship with the universal relation. Operations of the data hypercube such as slice, rotate, rollup, rolldown. Information technology and the concept of data warehouses. Architecture of data warehouses. Metadata repositories. Data Integration. The quality of the data warehouse. Data Aggregation. Data storage systems. Virtualization storage. Technology access to storage. Extracting data repositories. Data warehouses tools.
Assessment methods and criteria: Current control (40%): written reports on laboratory work, essay, oral examination; Final control (60% of exam): in written, verbally.
Recommended books: Шаховська Н.Б., Пасічник В.В. Сховища даних. — Львів: Магнолія-2006. 2008. — 487 с. Хранилища данных: шаги от идеи до внедрения, 2006, http://www.cnews.ru/newcom/index.shtml. Конноли Т., Бэгг К., Страчан А. Базы данных: проектирование, реализация и сопровождение. Теория и практика. 2-е изд.: Пер. с англ. — М.: Издательский дом «Вильямс», 2000. — 1120 с.

Analytical Data Warehouse (курсова робота)

Major: System Analysis
Code of subject: 6.124.01.E.088
Credits: 2.00
Department: Information Systems and Networks
Lecturer: Ph.D. Mykich Khrystyna Ihorivna
Semester: 7 семестр
Mode of study: денна
Learning outcomes: models and methods of designing and implementing data warehousing; decisions on technology data warehousing; the practical application of basic methods, tools and techniques of modern storage.
Required prior and related subjects: Databases and knowledge bases organization
Summary of the subject: The concept of data hypercube and its relationship with the universal relation. Operations of the data hypercube such as slice, rotate, rollup, rolldown. Information technology and the concept of data warehouses. Architecture of data warehouses. Metadata repositories. Data Integration. The quality of the data warehouse. Data Aggregation. Data storage systems. Virtualization storage. Technology access to storage. Extracting data repositories. Data warehouses tools.
Assessment methods and criteria: Final control (100%, term paper): defense of work.
Recommended books: Шаховська Н.Б., Пасічник В.В. Сховища даних. — Львів: Магнолія-2006. 2008. — 487 с. Хранилища данных: шаги от идеи до внедрения, 2006, http://www.cnews.ru/newcom/index.shtml. Конноли Т., Бэгг К., Страчан А. Базы данных: проектирование, реализация и сопровождение. Теория и практика. 2-е изд.: Пер. с англ. — М.: Издательский дом «Вильямс», 2000. — 1120 с.