The course is mainly focused on solving specific typical analytical and managerial tasks. The way of working in the course and the conditions of its successful completion correspond to this. The course is focused on various uses of Excel and Power BI tools, for the creation of virtual business data models and their possible visualization. It deals with the correct procedure of creating and evaluating different types of data. It emphasizes the work with appropriately designed data models and their managerial use. It focuses on the consistent creation of data models, including item calculations using appropriate methods and procedures. It shows the role of business data in their interaction and their importance for relevant management decisions. It shows how to proceed in the creation of data models of industrially oriented companies. It also includes the creation of the resulting dashboards for decision-making of managers at various levels. The prepared computer models are used to demonstrate important knowledge and connections.

1. The role of manager and analyst. Business Intelligence tools and their importance.
2. Basic management and analytical tools (methods, approaches, techniques, procedures, software support).
3. Description of the main economic objectives of projects / companies, economic and financial evaluation of project feasibility. Prediction of costs / revenues of projects / companies.
4. Business / project budgets and plans. Purpose, structure and procedure of creation and evaluation.
5. Basics of data collection and processing using tools - Power Pivot (Excel / Power BI), including basic creation of BI models.
6. Managerial work with budgets. Variants of corporate budgets. Their creation and evaluation with the help of BI.
7. Basics of calculations (DAX) for possible interpretation of information. Different needs of managers at different levels.
8. Calculations (DAX) and their use for business practice.
9. Basics of presentation of managerial information, including data manipulation.
10. Introduction to reports and dashboards. Measuring company / project performance. Determining indicators and their explanatory power - KPI.
11. Sensitivity analysis - identification of key economic and non-economic risks of the project and their impact on project implementation and its effectiveness, including measures to eliminate these risks.
12. Analysis of the resulting information of engineering projects / companies, focusing on orders, revenues, costs, productivity, scrap, etc.
13. Final part - project presentation.

1. Introduction to the course program. Rules of work before and at the seminar. Creating teams.
2. Introduction to creating business models in MS Excel using Monte Carlo tools.
3. Creation of the main economic goals of the project, economic and financial evaluation of project feasibility. Project cost and revenue prediction.
4. Implementation of corporate / project budgets and plans. Purpose, structure and procedure of creation and evaluation.
5. Basics of data collection and processing using tools - Power Pivot (Excel / Power BI), including basic creation of BI models.
6. Operating budget: creation of an operating / project budget based on the interaction of activities and their capacity, allocation of resources using BI tools.
7. Basics of calculations (DAX) for possible interpretation of information.
8. Calculations (DAX) and their use for business practice.
9. Basics of presentation of managerial information, including data manipulation.
10. Creation of reports and dashboards. Measuring business performance. Determining indicators and their explanatory power - creation of KPIs.
11. Sensitivity analysis - identification of key economic and non-economic risks of the project and their impact on project implementation and its effectiveness, including measures to eliminate these risks.
12. Analysis of the resulting information of engineering projects / companies, focusing on orders, revenues, costs, productivity, scrap, etc.
13. Final part - project presentation.

(1) FEW, Stephen. Show me the numbers: designing tables and graphs to enlighten. Second edition. Burlingame: Analytics Press, [2012]. ISBN 978-0-9706019-7-1.
(2) FEW, Stephen. Information dashboard design: the effective visual communication of data. Sebastopol: O´Reilly, 2006. ISBN 978-0596100162.
(3) Cokins, G.: Activity-Based Cost Management, John Wiley and Sons
(4) JONES, Daniel. Power BI: a comprehensive beginner´s guide to learn the basics of power BI from A-Z. [místo vydání není známé]: Daniel Jones, [2019]. ISBN 9781705354414.
(5) TAYLOR, Ivana a Bill JELEN. Excel for Marketing Managers. Uniontown: Holy Macro! Books, 2006. ISBN 1-932802-13-4.
(6) Philip Seamark. Beginning DAX with Power BI: The SQL Pro’s Guide to Better Business Intelligence, 2018. ISBN 1484234766.
(7) Ramesh Sharda, Dursun Delen, Efraim Turban. BUSINESS INTELLIGENCE, ANALYTICS, AND DATA SCIENCE, 2017. ISBN 9781292220543.

Prerequisites: Basic knowledge of using Excel. Requirements for students: Processing of all assigned tasks, their presentation and defense of solutions. Elaboration of semester work. Obtaining at least 50% from continuous tests. Prescribed course attendance.