Greg Strzyminski
Power BI Consultant & Trainer
Warsaw, Poland
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Greg is a Business Intelligence Team Lead at Kearney Warsaw. He serves as a Power BI technical Lead for Kearney.
He has proved his lecturing and teaching skills by running Power BI community events as well as internal trainings at Kearney at all levels, ranging in audience size from 5 to 250. Greg has been leading a number of Power BI workshops aimed at experienced professionals, students as well people willing to explore the art of possible in Business Intelligence. He has experience at conveying his knowledge at various levels, ranging from beginner to expert.
Greg holds a number of Microsoft Certifications including Power BI - related ones: PL-300, DA-100 and 70-778.
Area of Expertise
Topics
DAX window functions in practice
Window functions are a new addition to DAX launched in December 2022. They aim to simplify certain data operations which are very intuitive in Excel, but weren't so easy to replicate in DAX so far.
In this session we'll cover the 3 main window functions: INDEX, OFFSET and WINDOW to build meaningful insights. We'll see the power of these window functions by simplifying a previously lengthy DAX code and speeding up comparison-type analysis. We'll leverage the window functions to build a Pareto chart, a Cumulative chart and calculate delta comparing to last item.
Intuitive totals in Power BI
You’ve probably faced this already: counterintuitive value of the total in a table or matrix visual in Power BI. For example, the values from 2 visible rows are 20 and 30, so that is 50 when you sum it up. But the total keeps showing 200 for some reason.
But why is this happening? Can’t Power BI (DAX engine, to be specific), just sum up the individual cell values to compute the total? Well, the answer to this question is a bit more complex. But here’s the good news for you: the whole thing is quite quick and easy to solve once you know how to get onto it. If you don’t, then you might just as well spend hours trying to make the total display the expected value.
There is a number of scenarios, varying by complexity, that can lead to unintuitive totals. During this session we will explore them and see how to tackle each of the use-cases during a live demo. We will also brainstorm on the opposite side of the coin – that is, when it might not actually be a good idea to make the total more intuitive.
After this session you will:
• Know how to make the total intuitive in a number of scenarios varying by complexity.
• Understand why the totals are not always intuitive, but still correct.
• Be aware of what do the additive, semi-additive and non-additive measures have to do with the Power BI totals.
It would be great if prior to attending this session you would have a general understanding of DAX, dimensional modelling and would have created a couple of reports yourself.
Simplify your DAX with window functions
Window functions are a relatively new addition to DAX. They aim to simplify certain data operations that are very intuitive in tools like Excel, but weren't so easy to replicate in DAX so far.
In this session I'll introduce you to the 3 main window functions: INDEX, OFFSET and WINDOW. Even though their syntax may seem a bit complex at first glance, I'll show you that using them is not a rocket science. You will learn a number of real-life use-cases and code patterns that you can start using in your own Power BI reports from the very next day. Based on these use-cases, you will see the potential of window functions to not only simplify a previously lengthy DAX code but also optimize it in terms of performance. I will also introduce you to some 'false friends' of window functions - cases where it might actually not be the best idea to use them.
Selected use cases which you will learn include: time intelligence, running totals, cumulative calculations, Pareto charts and Excel-style calculations (e.g. delta compared to last item).
During this session you will:
- understand the concept and syntax of window functions in DAX.
- learn when to use window functions and when not to.
- discover a number of use-cases for window functions that you can immediately start using in your own work.
It would be great if prior to attending this session you have a general understanding of DAX and its key concepts.
Elevate the art of possible with the new card and slicer visuals
Over the past few months, Microsoft has been actively working on enhancing the capabilities of the built-in card and slicer visualizations in Power BI. A lot has been happening in this area, and you may have already heard about use cases showcasing these new features in action. But how do you go about leveraging these capabilities in your daily work? Where do you start, and what can you achieve without tearing your hair out?
In this session, I will guide you through the current functionalities of the new card and slicer visuals. You will see the new features based on real-life examples, which we'll build together during the session. I'll share a number of scenarios in which utilizing the new functionalities is a great idea, but also when it's better to stick to proven and established methods.
After this session you will be:
- familiar with the current capabilities of the new card and slicer visuals.
- able to identify scenarios in which using these functionalities will result in tangible benefits.
- equipped with the technical knowledge needed to implement the new card and slicer visuals in your reports literally the next day.
It would be great if before attending this session you would have basic experience working with Power BI and have had the opportunity to create various types of filters and cards in your reports.
Automate data ingestion with custom Power Query functions
Have you ever needed to ingest a number of same-structured inputs into your Power BI report and repeat the refresh periodically? If so, then it seems like a perfect use-case for automation using custom-made Power Query functions.
You might have already tried authoring such a function, as Power Query is often able to generate the whole thing automatically, in a user-friendly way. But what do you do if you need to handle a more complex scenario, include multiple inputs as arguments of the function or something has just stopped working and you're unsure how to fix it?
During this session you will learn the Power Query custom functions from A to Z. I will first show you how to identify a good use-case for this feature. Further into the session, you will learn how to create such functions from scratch as well as what are their semantics and components. I will explain how to effectively work with custom functions and debug them over a number of use-cases. You will also learn a number of common pitfalls and bad practices to avoid.
After this session you will be able to:
- recognize use-cases for automation using Power Query custom functions.
- create custom functions to handle complex scenarios.
- debug and optimize custom functions.
It would be great if prior to this session you have some experience working with Power Query and basic transformations within it.
Implementing VLS (Visual-Level Security) in Power BI
Have you ever wondered if it’s possible to implement varying access rights by visual? You’ve surely heard of RLS and therefore you know that a single given user can have just one role at a time, so just one scope of data access per user per report will work.
But how do you tackle a use-case, when the same user should have visibility into:
- only his/her region in one visual and the whole country in another visual.
- detailed sales data for his/her region in one visual and an aggregated finance data in another visual.
There may be some thoughts on how to address this challenge already lingering through your mind: a duplicate (likely aggregated) data model, leveraging OLS (Object-Level Security), creating another page with the aggregated data and restricting access to it by conditionally displaying a page navigation menu. While all of these methods do work to a certain extent, they also feature trade-offs and limitations e.g. introducing redundancy to the model, not being the most user-friendly, intuitive or robust.
During this session I’ll introduce you to another method of solving the said use-case: the VLS. This technique doesn’t come with any of the drawbacks mentioned before. I’ll first cover the concept behind VLS and explain how to implement it during a live demo. You will also learn a number of use-cases that can be tackled with it. Finally, I will go through a few potential pitfalls in VLS and how to work around them.
After this session you will:
- understand the concept behind VLS.
- be able to implement VLS in a number of scenarios.
- know good and best practices when working with VLS.
It would be great if prior to attending this session you would have a general understanding of RLS, DAX and tabular models.
Simplify your DAX with window functions
Window functions are a relatively new addition to DAX. They aim to simplify certain data operations that are very intuitive in tools like Excel, but weren't so easy to replicate in DAX so far.
In this session I'll introduce you to the 3 main window functions: INDEX, OFFSET and WINDOW. Even though their syntax may seem a bit complex at first glance, I'll show you that using them is not a rocket science. You will learn a number of real-life use-cases and code patterns that you can start using in your own Power BI reports from the very next day. Based on these use-cases, you will see the potential of window functions to not only simplify a previously lengthy DAX code but also optimize it in terms of performance. I will also introduce you to some 'false friends' of window functions - cases where it might actually not be the best idea to use them.
Selected use cases which you will learn include: time intelligence, running totals, cumulative calculations, Pareto charts and Excel-style calculations (e.g. delta compared to last item).
During this session you will:
- understand the concept and syntax of window functions in DAX.
- learn when to use window functions and when not to.
- discover a number of use-cases for window functions that you can immediately start using in your own work.
It would be great if prior to attending this session you have a general understanding of DAX and its key concepts.
Level up UX by leveraging advanced DAX
You've faced this - you gathered precise business requirements, designed efficient data ingestion into a carefully crafted star-schema, authored state of art DAX and beautiful visuals - all to receive a 'meeeh' from the client because they can't properly see the data label on the highest column in the column chart. Or because they picked a product from the product slicer only to face a completely blank report page and find out that this product isn't actually sold in the currently selected country.
I've been there too. And while putting a background in the data label solved the first problem mentioned at first (at least partly), I realized that this is not the ultimate solution we want to aim for. Neither was enabling a bi-directional relationship to fix the second problem.
Throughout my Power BI journey I've faced a number of these issues, all of them having two traits in common: they heavily hindered User Experience and could be solved by a bit of smart DAX. During the session I'll share these challenges and solutions to help you tie up the last loose ends in your report. And impress your client - be the client external or your boss.
After the session you will be able to:
• Improve the scaling of charts
• Create visuals with custom labels using different approaches
• Limit the number of options in slicers to only those available in current context without resorting to bi-directional relationships
Before you join this session it would be great if you have a good understanding of DAX concepts and dimensional modelling in Power BI.
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