Business Intelligence and Business Process Analytics

Enhance knowledge and skills that can be applied to:

• Effectively manage and improve sales and customer management metrics;
• Automate project profitability calculations;
• Provide the team with essential tools that save time and support daily decision-making;
• Assist in planning efficient warehouse operations;
• Ensure quality management and workflow efficiency;
• Digitalize business processes and model business data flows;
• Understand company cycles and digitalization needs at different growth stages;
• Automate the creation of company reports and summaries;
• Implement strategic management indicator monitoring, forecasting, and management methodologies;
• Leverage BI capabilities to maximize long-term benefits.

• Business owners;
• CEOs;
• CFOs;
• Department and project managers;
• Aspiring and existing business analysts;
• Anyone who wants to learn more about how to use the benefits of BI to their advantage, working even more productively and efficiently.

• Understand the importance, capabilities and application of BI in business process analysis and management.

• Independently analyze your business and improve business processes.

• Formulate the needs of your business or department in terms of digitalization and automation.

• Communicate your business analytics needs in a structured and understandable way.

There are no specific prerequisites.

Instructor-developed training materials, access to the business analytics platform flex.bi, and a list of useful literature.

Not intended.

1. Basic BI concepts and operating principles.
2. History of BI platforms and technical differences.
3. Application of BI in company management and business process optimization.
4. Company experience stories: Sales management, budget control, project profitability calculations, warehouse, customer relations, embedded analytics and team motivation.
5. Company business processes and data flows.
6. Business process modeling and digitalization.
7. Differences between accounting systems and integrated business management platforms ERP.
8. Business management systems and their technical operating principles (ERP, CRM, Project Management, etc.).
9. Data cubes, databases and other types of data storage.
10. System compatibility and IT infrastructure evaluation from a business analytics perspective.
11. Indicator selection methods.
12. Key performance indicator (KPI) libraries.
13. Company life cycles.
14. Analytics levels (descriptive, predictive, prescriptive).
15. Sales analysis – indicators and formulas.
16. Workflow analysis.
17. Financial indicators and their application.
18. Project profitability analysis.
19. BI implementation process.
20. User requirements and specifications of the pivot tables
21. BI success factors and technology adoption.
22. Data literacy. A
23. pplication of artificial intelligence (AI) in business analytics.