Qlik vs. Power BI: Part 1 – A Hands-On Comparison

At Bitmetric, we are widely known as Qlik enthusiasts. Our Friday Qlik test prep questions are famous in the Qlik world , as well as our well-read Blogs. But just like Qlik, we’re equally curious about other tools in the BI and analytics space, like Databricks, TimeXtender, Microsoft Fabric, or Power BI. 

Recently, I worked on a large enterprise-level project. The work involved migrating several dashboards from Qlik Sense (Enterprise Client-Managed) to Power BI.

I had previously led both Power BI and Qlik Sense projects. I also managed a migration from QlikView to Power BI, where we moved all logic into a data warehouse at the same time.

Because I already had extensive knowledge of the data models behind the Qlik Sense dashboards, this project gave me a rare opportunity. I was able to compare the same data models, transformations, and visualizations across both platforms side by side.

So what did I learn? Where does Power BI shine, and where does Qlik still hold the edge? Over the next few weeks, I’ll share my findings in this blog series.

Why This Series? 

There’s no shortage of high-level comparisons between Qlik and Power BI. The Gartner Magic Quadrant, for example, has consistently placed both vendors in the Leaders quadrant for years. While these strategic overviews are useful, they don’t tell you what it’s actually like to work with these tools day to day. 

And that’s what this series is about: a practical, hands-on comparison based on real development work. I’ll focus on three apps we rebuilt in Power BI, covering the transformation steps, data modeling, scripting, and front-end design. I’ll also touch on the end-user experience and integration with other tools from a user perspective.  

To keep things focused, this comparison is limited to: 

• Power BI Desktop + Power BI Service 

• Qlik Sense (Enterprise Client-Managed) 

Microsoft Fabric and Qlik Cloud were not in scope for this project. Many insights also apply to Qlik Cloud Analytics. I will sometimes mention features in Qlik Cloud that are not in Client Managed. Cloud features like Qlik Automate or Qlik Predict are out of scope, as are Fabric features.

For Who is this Series? 

This series is for anyone facing the question: “Should we go with Qlik or Power BI?” or if you are looking for a Data Analytics tool in general. Whether you’re a data analyst, IT manager, or business stakeholder, these posts are written to help you make a grounded, experience-based comparison. 

You’ll benefit most if: 

• You’re considering migrating from one platform to the other 

• You’re evaluating tools for a new BI environment 

• You’re working in a hybrid setup and want to understand the trade-offs 

• You’re a developer curious about how the same logic translates across platforms 

Rather than focusing on marketing claims or feature checklists, this series dives into real-world development, modeling, and user experience, the things that actually matter when building and using dashboards. 

A Fair and Honest Perspective 

Choosing between Qlik and Power BI often depends on organizational needs and personal preference. I’m not a fan of just one tool. Having worked with QlikView, Qlik Sense, and Power BI, I can say I like them all.

Both Qlik and Power BI are mature analytics platforms that improve decision-making when used well. They cover the essentials: charts, KPIs, tables, scheduled refreshes, and many connectors.

Both embrace AI and have active communities where you can find support. In the end, the quality of your data model matters more than the tool itself. What does set them apart in daily use is what this series will explore.

Cost  

Obviously when choosing any software platform, cost is a deciding factor. In this series, cost is not in scope, as we are focusing on day-to-day usage of the tools.  Another reason is that a cost comparison is very use-case specific. While you will find numerous license cost comparisons online, the reality is that license comparison is tricky, as Qlik and Power BI have different license models and just looking at the per-user cost alone will not give the full picture.  

Well known is that the start-up cost of Power BI is low, with its €13/month Pro license. However, as usage grows, most organizations will need to upgrade to Fabric Capacity (previously Power BI premium) at some point. In this license model you pay for capacity, and which tier you need is dependent on numerous factors such as usage, data model size and fabric elements that you use. There are some features in the Power BI service, that are only available for Fabric capacity or Premium-per-User licenses.  
This license form makes it harder to compare on a general level, specifically because for Qlik Cloud, there is also a capacity model (where pricing is mostly based on the size of your data). So in both cases, the way your environment and your data is set-up has a big impact on costs.  

On top of that, license costs alone will not give a full picture. The total cost of ownership (TCO) of your analytics solution will depend on more factors than licensing. For example, If you choose Qlik Sense Client Managed instead of Qlik Cloud, you have costs for the server it runs on. For Power BI, report developers will most likely work in Power BI desktop, which needs a Windows laptop with enough CPU and memory, and it means they will locally connect to data sources, for which infrastructure will be needed.  

Ultimately, TCO is often influenced by how productive end-users and developers can be on a day-to-day basis. If the environment or data structure is complex it will take a developer more time to add visuals to a production dashboard, ultimately leading in lesser additions that could be done in a given timeframe, or more developers needed for the same output. Other factors could be environment size, data model performance, skill level of developers and the number of end-users.  

Infrastructure Integration 

Integration can also be a deciding factor. If your organization already has substantial infrastructure in Microsoft Azure, Power BI can be a logical choice. It integrates natively with Azure services and automatically leverages Microsoft Entra ID (previously Azure Active Directory) for user access, saving your infrastructure team time and effort on authentication and integration. 

On the other hand, if your organization has strict security or compliance requirements that limit cloud adoption, Qlik Sense Enterprise Client-Managed remains a robust and fully supported alternative. It offers the flexibility of on-premise deployment while still benefiting from Qlik’s powerful associative engine. 

What’s Next?  

In this first article, I gave an outline of what to expect, why I am writing this, who this series is for and what the scope of this series is. Over the next weeks, I will cover the following aspects:  

Stay tuned!  

Explore the full series:

Part 1 : 4 September 2025: Back-End and Data modeling 

Part 3: 11 September 2025: Front-End development and user experience  

Part 4: 18 September 2025: End-user interaction & Integration