Jiří Neoral
Microsoft MVP | BI Architect at DataSentics | Power BI & Fabric
Brno, Czechia
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I am a Microsoft MVP for Data Platform (Power BI) since 2017, BI Architect & Consultant at DataSentics, and a long-time trainer at GOPAS. Since 2008 I have been working with the Microsoft BI stack — from classic SSAS through Power BI to Microsoft Fabric. Recently I have been deeply focused on AI-assisted development: leveraging MCP Server, GitHub Copilot, and Claude Code for agentic semantic model and report generation, including conversion from DBT. I speak on these topics at community conferences and share insights on this blog. Outside of data: gyrocopter pilot, ex-Ironman triathlete, father of two kids and a dachshund.
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Power BI and SSAS better together
Microsoft Fabric introduces capabilities for handling data from the source to the presentation layer, with OneLake serving as a unified data storage solution. But are there still valid use cases for 'old' technologies like SSAS?
In this presentation, you'll discover whether SSAS still has a place in modern data architectures and how to leverage it for the benefit of you and your company.
Mastering DAX and beyond
DAX is a powerful tool in the arsenal of every Business Intelligence developer working within the Microsoft ecosystem. However, like any tool, it must be used wisely—great power comes with great responsibility.
Beyond Power BI, DAX knowledge is transferable to Analysis Services (both on-premises and in the cloud) and Excel’s Power Pivot, where its journey first began.
Who should attend?
This workshop will be conducted in Czech language and is designed for anyone working with DAX—whether you’re a beginner looking to build a strong foundation or an advanced user aiming to refine your expertise.
You’ll gain new insights, practical experience, and hands-on learning to improve your DAX skills in real-world scenarios.
1. DAX Language Essentials
Key concepts and best practices
Practical examples of DAX applications
How DAX is used across different Microsoft platforms
2. Effective DAX Usage in Various Scenarios
Calculated Columns vs. Transformations: When to use each
Understanding Measures: Their role in different scenarios
Calculated Tables: When to use them—and when to avoid them
Row-Level Security (RLS): Implementing secure data access with DAX
Performance Optimization: Enhancing VertiPaq storage and memory efficiency
Debugging & Performance Tuning: Fixing slow reports and optimizing performance
3. Hands-on DAX Development
Solve real-world problems with hands-on exercises
Improve fluency in DAX, data modeling, and reporting
Apply practical examples to enhance understanding
Key Takeaways
By the end of this workshop, you will:
Understand when to use Calculated Columns vs. Measures
Learn common pitfalls to avoid in DAX
Design efficient data models with performance in mind
Develop techniques for analyzing and debugging performance issues
Gain a wealth of practical examples to apply in your work
And most importantly—have an engaging and productive learning experience!
Jiří Neoral
Microsoft MVP | BI Architect at DataSentics | Power BI & Fabric
Brno, Czechia
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