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Why DAX?
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Speakers
Explore speakers' bios and topics.
Power BI
Best practices for developing Power BI reports
In this session we will look at the most important best practices when developing a Power BI report and how these best practices can improve our life as developers.
We will differentiate best practices in the following three areas:
- Power Query / M
- Data modeling & DAX
- Visualization
Within these areas, we will see which best practices have an impact on performance and which ones help you to better organize your artifacts and improve usability of the report and readability of your code.
Remember that best practices are mostly not for you, the developer who has built this report. The main benefit is if we open a report from someone else or inherit one from a colleague, that is when you will start appreciating people following best practices.
Won’t you appreciate being handed over a nicely organized report that fullfils the most important best practices? Make it your mission to stand by them when you build Power BI reports.
Power BI
Star Schema ALL the things! But why?
Perhaps you’ve seen “Star Schema ALL the things!”, “Never use Calculated Columns”, or “Bi-Directional relationships suck” before when thinking about design considerations for your data model, but you’ve never really stopped to think about the specifics behind them and why exactly they could benefit or hurt your model. Who knows, maybe that specific advice doesn’t even work out for the scenario at hand and you might not be aware because you’ve skipped a few steps in the process.
Come along in this journey from source to model to report using a practical mindset, thinking about the design decisions and ramifications along the way. At the core of the session lies the message to think about best practices, with the added step to test, assess, and benchmark what exactly they do for you.
Whether it be the decision of where your transformations need to be done, how exactly the data and tables need to be modelled or what you allow the end users to do with your model these are all important steps to take, preferably without shortcuts. We’ll take the steps on a moderately complex data model, and measure as we move along.
Meaning, at the end of the session we’ll have discussed why Star Schema’s can help you, and how you can assess for yourselves if they are beneficial for your use case.
Fabric
Efficient Data Partitioning with Microsoft Fabric: Best Practices and Implementation Guide
Imagine having a vast encyclopedia, and your task is to find a specific page containing a particular word. Instead of searching through the entire encyclopedia, you opt to navigate directly to the relevant section that might contain the desired information. This approach allows you to narrow down your search scope and quickly find the page you need. This concept of narrowing down the search space by dividing data into manageable sections is precisely what partitioning entails.

Power BI
A delightful Power Concert
In this session I will show you different ways of building a Power concert where we make the different instruments in the Power Platform band play together in a perfect harmony.
I will demo how can we make Power Apps and Automate drive actions from directly in Power BI and how we can connect Power Apps to Power BI reports and how to get data from Power BI into Power Automate.
Combining these instruments will enable you to play power full tunes that will make your users sing along.
It will be a demo heavy session that should give you inspiration to compose your own power tunes 🙂

Power BI
From XL to S – Reduce your Power BI model size by 90%!
Have you ever wondered what makes Power BI so fast and powerful when it comes to performance? So powerful, that it performs complex calculations over millions of rows in a blink of an eye.
In this session, we will dig deep to discover what is “under the hood” of Power BI, how your data is being stored, compressed, queried, and finally, brought back to your report. After the session, you will get a better understanding of the hard work happening in the background and appreciate the importance of creating an optimal data model in order to get maximum performance from the Power BI engine.
Finally, you will see a real use-case demo showing how the Power BI data model was reduced by 90%!
I will demo how can we make Power Apps and Automate drive actions from directly in Power BI and how we can connect Power Apps to Power BI reports and how to get data from Power BI into Power Automate.
Combining these instruments will enable you to play power full tunes that will make your users sing along.
It will be a demo heavy session that should give you inspiration to compose your own power tunes 🙂

Power BI
C# Scripts for Tabular Editor are not that tough: Bringing Visual Studio into the party
If you are not a C# Jedi, trying to write C# scripts for Tabular Editor in Tabular Editor 2 is quite of a challenge. At least it was for me. With time I found out how to bring development over to Visual Studio, and how to bring the code back easily into tabular Editor. In this session I demo how to set up the environment and start coding away in a much more confortable way.
Power BI
Citizen data analyst hitchiker guide to Power BI
You are passionate about data analysis and ended up installing Power BI, but what now? where to go, and what are all those terms?
Don’t worry, this session will guide you through the Power BI language.
What’s the difference between the Direct Query and Live Connect? Then…Data…Dataset – Dataflow – Datamart…What are all these?! “I’ve created a wonderful dashboard”. You mean, report? No…yes…I don’t know the difference ☹
Can I use DAX to create calculated columns in Power Query? And, how to create measures in Power Query? (No, you can’t do that, it’s a different language). I’ve installed the data gateway, now I need to choose the proper mode – I should go with personal, right?
In this session, we will demystify the most common sources of confusion among Power BI practitioners and explain differences and similarities between various Power BI terms and concepts. You’ll walk away with a clear understanding of the terminology and feel more confident talking Power BI!

Fabric, Power BI
Exploring Fabric Semantic Link for Power BI folks!
If you’re coming from a Power BI world, the whole Fabric thing might scare you a bit. Then suddenly, there is something called Semantic Link, which allows connections from Fabric Notebooks to read both data and meta data from your Power BI Semantic Model (dataset).
You might wonder, what’s all this? How does it work and how to take benefit from it? Especially when you’re not familiar yet with notebooks at all.
In this session we will explore what Semantic Link is, how you as Power BI developer/engineer can make use of it and how it will strengthen your solutions in the end. Together, we will explore various aspects like:
- Warming up your data in direct lake datasets
- Querying Dynamic Management Views,
- Reading Semantic Model meta data to generate documentation
- Extend or even forecast your data using Semantic Link
By the end of this session, you will not only grasp the basics of Semantic Link but also gain practical insights into its application so you can bring it to practice directly!

Fabric
Make Fabric the Gold layer of your multi-cloud medallion architecture!
While Microsoft Fabric is a full-blown data platform in its own right, you might allready have invested in a modern data platform allready.
You still use Power BI of course – because that is the best tool out there.
That might come with a cost – such as slower reports or egress costs. Or you might miss out on some new functionality in your current solution that Fabric promises to deliver.
Microsoft has got you covered!
Come join me to see how Fabric can be positioned as your gold layer – or part of the gold layer in your data platform.
We will look at data mirroring, shortcuts, and all the nice little tricks available to get the best of both worlds: Your existing data platform and Microsoft Fabric!
Key take-aways:
Learn how Fabric can integrate with solutions such as Databricks, SQL dwh or Snowflake to give you the best of both worlds.
Learn how data mirroring works in the different systems.
Understand how shortcuts and OneLake APIs can help you.










