Qlik vs Power BI: Part 3 – Front End Development & User Experience 

Welcome back to Part 3 of our series on Qlik vs Power BI.

If you are new, Part 1 covered the why and the who, and Part 2 walked through the back end and data modeling, how data is loaded, transformed, and structured.

Today we dive into the front end where dashboards come to life, comparing Qlik and Power BI on layout and styling, expression languages, interactivity, and how each tool supports developers and end users.

Let’s dive in!

Front-End Development and Styling 

In the front end, the developer builds up the dashboard that end users interact with. Developers will use expressions to build formulas on top of the data model and show the results in KPI charts, bar and line charts, and other visualizations. You will be able to build beautiful looking dashboards in both Qlik and Power BI, as both of these platforms have all the essentials of a modern BI platform. However, the way you achieve that is quite different.

Layout and Responsiveness 

Layout is one of the most noticeable differences in the Qlik vs Power BI Front-End. Qlik Sense uses a grid based, responsive layout. You drag and drop charts into a grid and resize them within that structure. This makes it easy to align KPIs and visuals and ensures a consistent layout across screen sizes. However, it can also limit creative freedom when you need precise control over positioning and sizing.

To address this, Qlik introduced the Layout Container, which allows for pixel perfect placement of objects within a defined area. This bridges the gap between flexibility and structure, giving developers more control without abandoning the responsive grid entirely.

Qlik’s Grid sheet layout.  

Power BI, on the other hand, has always been about precision layout. You can place visuals exactly where you want them, down to the pixel. This offers a lot of freedom, but it also means you will spend more time manually aligning and resizing elements. The key to success here is starting with a well designed template and sticking to consistent measurements throughout development.

Power BI’s page layout.   

Both tools face challenges when it comes to screen resolution differences. Even though Qlik is responsive, you will not always agree with the way the objects are sized or rearranged on screens that have a different resolution than the one the report was built in. With Power BI, you might find that users with higher screen resolutions will see more white space than you would like.

For mobile screens, Power BI allows you to create a dedicated mobile layout, where you can cherry pick visuals from the desktop version and rearrange them for mobile screens. In the Power BI mobile app this will be the standard layout. In Qlik, this typically requires building a separate app for mobile use.

Power BI Styling and Customization 

When it comes to visual polish, the Qlik vs Power BI Front-End offers developers different levels of control.

Styling options have historically been more extensive in Power BI. You can customize nearly every aspect of a visual, colors, fonts, borders, backgrounds, and more. However, the core visuals (bar charts, line charts, scatter plots, etc.) have seen limited improvements in recent updates. Microsoft is focusing on Fabric integration and Copilot, while users still ask for long-awaited core visual improvements.

For example, conditional formatting works for many elements and visuals but is not consistently available across all of them, and some limitations remain. Recently, the Power BI core visuals team introduced a vision board outlining future improvements, which suggests upgrades are on the horizon.

Heavy use of styling options, with or without conditional formatting, often leads to copy-pasting logic. I keep a notepad with my most-used HEX codes, since switching visuals can reset colors to the template default. You could solve that by adding the right colors to a template, but you will not always have the freedom to that in an enterprise environment. Next to that, you might sometimes want to use colors that are not the standard colors in the template. Power BI offers copy-paste formatting like Excel and Word, but it misses some options and works inconsistently across visuals.

A stand-out feature that I love in Power BI, is the ability to create a report page as a tooltip and reference that from almost any visual. The tooltip will be filtered from the datapoint that the user highlights.  

A Power BI line chart with a page tooltip containing 3 KPI’s and a bar chart.  

Qlik Styling and Customization 

Qlik has made significant strides in styling over the past year. While some visuals are still lacking all style options you’d like, recent updates have introduced more granular control over fonts, colors, and layout behavior. What I like here, is that you almost always have the ability to conditional format based on an expression, in which you can also reference master measures or variables.

This gives you complete dynamic control while, if implemented well, keeps the ability to quickly change color or formatting options centralized. This is not available for all formatting options, but for example colors or chart titles are always available to dynamically change which really gives a dynamic touch to your charts.  

In Qlik you can also create dynamic tooltips, you can show extra measures or add visuals to tooltips, but since you cannot tooltip an entire page, it is a bit more limited than Power BI ‘s approach.  

Qlik also supports themes, which can be defined globally or per app. These themes allow you to set default fonts, colors, and spacing, helping maintain a consistent look across dashboards. 

With regards to improvements, Qlik has an active and vocal user community as well which speaks out when core features lag behind. For example, Qlik’s new straight table has received mixed feedback due to missing functionality that users relied on in the classic version, leading recently to Qlik reverting a planned deprecation of the old table. Another example is that in a recent update, Qlik added the option to add custom CSS to Qlik Cloud sheets, following criticism from the community after the deprecation of the Multi KPI object was announced. 

Extensions and External Visuals  

Both platforms support external visuals, though the implementation differs.

Power BI provides extensions through AppSource, its official store for custom and enhanced visuals. These update automatically in both Power BI Desktop and the Service. Some are free, while others require extra licensing.

Notably, visuals like Deneb allow you to build completely custom charts, although this requires learning a new language. For even more advanced use cases, you can create your own AppSource visuals using Node.js.

Qlik Sense supports extensions through nebula.js, which can be used to add new visuals or enhance user interface functionality. The library of available extensions is vast, with both free and licensed options.

However, Qlik lacks a centralized, well maintained store. In the QlikView days, Qlik Garden filled this role, but it was never updated for Qlik Sense. The community driven “Regarden” exists, but it needs more attention. Unlike Power BI, administrators in Qlik must manually track and update extensions.

A distribution plot in Qlik Sense.  

As an example, a distribution plot in Qlik could not be reproduced in Power BI using only core visuals. It could be recreated with Deneb or other extensions, provided administrators allow their use. In our case, we opted to present the data differently instead.

Development: Expressions, Measures, and Interactivity 

Expression Languages: DAX & M vs Qlik Script

One of the most fundamental differences between Power BI and Qlik lies in their expression languages.

In Power BI, the back end (Power Query) uses M-code, while the front end uses DAX (Data Analysis Expressions). These are completely different languages with separate syntax, logic, and learning curves. This separation can confuse new developers when moving between transformation logic and visual calculations.

DAX is closer to a formula language than a programming language, similar to Excel formulas. This makes it approachable for Excel users, though building a Power BI report is still very different from working in Excel. Writing DAX essentially creates queries against the data model, executed whenever a user interacts with a visual. Mastering DAX requires understanding filter context (filtering the model) and row context (expressions evaluated at the level of a row in a table)

Qlik, by contrast, uses the same scripting language in both the back end and front end, Qlik script. This consistency reduces cognitive load and allows for easier reuse of logic. Qlik script is a scripting language with similarities to SQL. When building visualizations, every expression interacts with Qlik’s associative model, where all objects are connected.

Master Measures and Reusability 

Power BI has long embraced the concept of centralized measures. You define your DAX measures once in the model, and reuse them across visuals. This promotes consistency and makes maintenance easier.

A common best practice is to create a measure table with no data, holding all measures instead of mixing them in data tables. In Power BI this requires a workaround, since there is no official centralized place for measures. The workaround is simple, but it is odd that Microsoft has not built this in.

A measure table in Power BI, with some measures grouped in a folder.  

Qlik has historically leaned more toward visual-level expressions, especially in the QlikView era. However, with Qlik Sense, the introduction of Master Items (including Master Measures) has brought it closer to Power BI’s approach of centralized measures. A key strength is that you can reference master measures in chart expressions, avoiding separate master measures for small filters.

Master Measures in Qlik  

Interestingly, Power BI is now adding features in the opposite direction with Visual Calculations, allowing users to define logic directly within a visual, similar to how QlikView developers used to work. As of date, you can only use these visual calculations in fields in the visuals, and not in titles, for example. Next to that, you cannot reference data model fields, but only fields that are in the visual. This makes it mostly usable for things like a quick running sum or % change calculation. However, Microsoft is adding more and more features to visual calculations recently, so the future might bring more useful additions.  

Measure Volume and Management 

In Power BI, you often end up creating more measures than in Qlik. This is partly due to DAX’s structure, since dynamic elements like chart titles need a centralized DAX measure. In Qlik, you can do this centrally, but often achieve the same with a simple chart expression or variable. In Power BI, you can group measures in folders to keep your data model clear for yourself and other developers.

Qlik has a dedicated menu for Master Measures, which Power BI lacks, and I miss the folder grouping there. Without proper naming convention, your Master Measures menu could get messy and the purpose of centralizing logic would be gone.  

Even though you’ll need more measures In Power BI, a big benefit is you can quite easily filter a table with a simple field filter on the visual in the filter pane, whereas in Qlik, traditionally this would require you to write code (probably Set Analysis) in the expression itself. Interestingly, Qlik recently introduced a similar feature to Qlik Cloud, making it more accessible for developers less comfortable writing set analysis syntax.  

Interactivity and Conditional Logic 

We will also touch upon interactivity in Part 4, where we focus on the end-user. However, interactivity should already be considered when developing the front-end, and even the back-end.

Interactivity in Qlik

In Qlik, every interaction of a user on a visual filters the associative model. Any selection in a chart or a filter pane always leads to a selection in the data model, and then influences all other visuals, on all pages. As the app author, you can adjust this with Set Analysis, which defines selections for a visual. For example, you can create a KPI that always shows Sales in 2025, no matter what other fields are selected.

A Qlik set expression, filtering the Sales Amount measure with the maximum year.

It’s important to note that in Qlik, as a result of the associative model, you don’t control visual-to-visual interactions directly. Instead, you influence how fields in the data model interact. The result could be the same for the end-user, but the logic behind it is different from Power BI, and therefore the way you develop it is also entirely different, making some things harder and others more easy.  

Interactivity in Power BI

Power BI’s data model is query based. With every click a user makes on a report, it is essentially querying the underlying data model. This may sound like a technical detail, but it is an essential difference, as it influences how users can interact with data. To control how visuals interact with each other, you use an overlay, where you can choose whether a visual filters, highlights, or ignores another.

The visual interaction overlay. The  Year slicer is set to filter the Total Revenue line chart but not the Total Profit line chart.  

Combined with drag-and-drop filters, that you can hide for end users, this makes it relatively easy to create visuals that are always filtered and not influenced by other visuals.  
 

Conditional Visibility

One area where Qlik still has a clear edge is conditional visibility.

In Qlik, you can show or hide objects based on: 

• User selections 

• Variables 

• Section access rules 

This allows for highly dynamic dashboards that adapt to the user’s context.  
 
In Power BI, conditional visibility is limited. In the Power BI service, you can show or hide reports for user groups with Audiences. This does not work at the page level. For charts, bookmarks can be used to simulate different views. However, visuals cannot be shown or hidden by selections or roles without complex workarounds. This remains a limitation compared to Qlik’s flexibility

Conclusion: Design Freedom vs. Development Discipline 

Overall, this Qlik vs Power BI Front-End comparison shows the trade-off between design freedom and development discipline.

For front-end development, Qlik and Power BI are both powerful but support different dashboarding styles.

• Power BI gives you pixel-perfect control and deep customization options, but it requires more upfront planning and manual effort to maintain consistency.  

• Qlik Sense offers a responsive, grid-based layout that makes alignment and structure easier, with growing flexibility thanks to features like the layout container. Styling options are increasing, but are currently more limited in comparison to Power BI.
   

In terms of development, Power BI’s split between M and DAX can be a hurdle, but that hurdle might be lower for users familiar with Excel formulas. Meanwhile, Qlik’s unified scripting language offers a smoother learning curve, but only once you’re familiar with it. Both tools offer centralized measure management, but there are some differences in usability and implementation.  

Both tools are evolving, and both have their quirks. The key is understanding how they align with your team’s workflow, your users’ needs, and your organization’s goals. 

Coming Up Next: End-User Interaction & Integration 

In Part 4 that will be available on 18 September 2025 , we’ll shift focus to the people who matter most: the end users.

We’ll explore how Qlik and Power BI handle: 

• Selections and filtering 

• Drill-downs and interactivity 

• Exporting and sharing 

• Integration with other tools (Excel, Teams, PowerPoint, etc.) 

If you’re evaluating these platforms not just as a developer, but as someone responsible for user adoption and business impact, this next post is for you. 
 
Stay tuned!