English

Not applicable.

Of all faculties

Students obtain knowledge about general principles on which the BI tasks are based, about the approach in their solution and using in the managing of the company gnd gain practical skill with analytics parts of BI.

The requirements for students are accentuate to level of knowledge database systems, data warehouse and the basic of programming language.

Not applicable.

The course contains lectures that explain basic principles, problems and methodology of the discipline, and exercises that promote the practical knowledge of the subject presented in the lectures.

Prerequisites:
Student during the semester must obtain at least 50% of the possible maximum, that is 20 points out of 40. If could be detected plagiarism or unauthorized collaboration on projects, or at mid-term test, credit will be granted with consideration of disciplinary proceedings.
Mid-term test - writing, (correct answers could be by selecting one of several sentence answers or a combination thereof), and developing practical task by task. There is no trial. (20 points)
Elaboration the project - a project by entering the appropriate documentation. The project proposition is introduced to students in the second lecture. (20 points)

Test conditions:
Final exam - written test form (correct answers could be by selecting one of several sentence answers or a combination thereof) and an oral examination. (60 points for the written part of the exam; for the successful completion of the exam must be written exam developed to be evaluated by at least 30 points, otherwise the test is scored 0 points with the evaluation of F.)

Předmět podává přehled o principech a přístupech k řešení Business Intelligence (BI), Cílem je získání nových znalostí a dovedností v BI a možnosti jejich využití v řízení podniku. S využitím moderních metod a softwarových nástrojů podporující analytické, plánovací a rozhodovací činnosti podniků tak vytváří předpoklady pro plnění funkce analytiků a konzultantů aplikací určených pro podporu rozhodování v podniku. Fundamentals of Business Intelligence, BI development, role in the architecture of IS / ICT, links to other applications.
1. Basic principles of MS Analysis Services features and capabilities (integration processes, data cubes)
2. Principles of dimensional modeling, dealing with the relationship of indicators and corresponding dimensions, physical design and modeling, data quality management.
3. Principles of implementation of BI, Data Pump, ETL - principle.
4. The OLAP technology (On Line Analytical Processing).
5. Application areas of BI, specification of application areas, the use of BI in business management, effects of BI applications.
6. Database environment, data warehousing environment - MS SQL Server-principles, architecture, individual components.
7. Management of BI tasks, effects and critical success factors of BI, planning and analysis of BI.
8. Solutions BI client applications, MS Office - Excel, Access,
9. Export OLAP cubes - off-line, query resources into multidimensional databases.
10. Basic principles of MS Analysis Services features and capabilities (Data Mining)
11. BI market segmentation, BI trends and examples of BI products.
12. Legal aspects of data protection.

Not applicable.

The goal of the subject is to teach students manage the projects, development and applications of Business Inteligence (BI), implementation of tasks BI and gain practical skill with analytics parts of BI.

The checking results of individual tasks. In case of excused absence in practical lessons the teacher can give compensatory condition.

Attendance at lectures is not compulsory. Seminars with computer support is required, attendance is controled. One absence from seminars could be apologized by teacher. Student will replace this lack of elaboration especially given homework.

Exercise with computer support are focused on teaching integration, analysis and prediction capabilities and tools of MS SQL Server. During the semester students write semester test for a maximum of 20 points. For this semester there is no test trial. If a student has a well-documented and teacher excused absence in seminars, where is written midterm exam, he/she can attend on an alternative date.

In the second lecture is given to students separate project for a maximum of 20 points. Student must obtain at least 10 points to recognize this project. The project student submits the credit week.
Students who have an individual learning plan, ie. they do not go into sečminars, have to prepare and submit a special stand-alone project for the credit. For this particular project can get 30 points.

The course ends with a written exam for a maximum of 60 points. Participation in the test is mandatory.

Not applicable.

Not applicable.

DECKLER, G. and B. POWELL. Mastering Microsoft Power BI: Expert techniques to create interactive insights for effective data analytics and business intelligence. 2nd ed. Pact Publishing, 2022. 712 p. ISBN: 978-1-80181-148-4. DECKLER, G. and B. POWELL. Mastering Microsoft Power BI: Expert techniques to create interactive insights for effective data analytics and business intelligence. 2nd ed. Pact Publishing, 2022. 712 p. ISBN: 978-1-80181-148-4. (EN)
SHARDA, R., D. DELEN and E. TURBAN. Business Intelligence, Analytics and Data Science: A Managerial Perspective. 4th ed. UK: Pearson, 2019. ISBN: 978-9353067021. (EN)

EDENFIELD, O. and E. CORCORAN. Microsoft Power BI Data Analyst Certification Guide: A comprehensive guide to becoming a confident and certified Power BI professional. Pact Publishing, 2022. 398 p. ISBN: 978-1803238562. (EN)
RUSSO, M. and A. FERRARI. The Definitive Guide to DAX: Business Intelligence for Microsoft Power BI, SQL Server Analysis Services, and Excel. 2nd ed. Microsoft Press, 2019. 768 p. ISBN: 978-1509306978. (EN)
SHARDA, R., D. DELEN and E. TURBAN. Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support. 11th ed. Pearson, 2019. 832 p. ISBN: 978-0135192016. (EN)