Compare Qlik Cloud® Analytics vs Power BI

Get this in-depth comparison of two top BI tools, plus practical advice to help select the right solution for your organization.

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Compare Qlik vs Power BI : Analytics Evaluation Guide

On the surface, both Qlik Cloud Analytics and Power BI appear to be robust solutions capable of handling all of your analytics needs. However, when you look beyond the basics, differences quickly begin to emerge. 

Power BI Pro is a strong data visualization tool for authors to create and share content. While Qlik similarly satisfies the needs of authors, the real magic of Qlik Cloud Analytics is that it also delivers big benefits to data consumers. Qlik’s unique associative data engine is a key differentiator, allowing users to freely explore data relationships and uncover insights that query-based tools might miss. It’s the combination of that engine with the Qlik platform where glaring differences begin. While you can’t scale Power BI Pro without adding more products from the Microsoft stack, Qlik Cloud Analytics can be scaled as is — all on the same platform. 

This beyond-the-surface guide compares Qlik Cloud Analytics to Power BI on 15 key factors. 

Attribute

Qlik Cloud Analytics

Microsoft Power BI 

Advanced Data Visualization 

✔️ Comprehensive out-of-box visualization library

✔️ Rich visualization capabilities

Interactive Dashboards 

✔️ Native, intuitive interactivity

⚠️ Basic interaction and limited exploration

Total Cost of Ownership  

✔️ Customizable plans, capacity-based pricing, no hidden costs as you scale

⚠️ Affordable for individual or small teams, but costs increase with scale

Augmented Analytics 

✔️ Foundationally integrated AI assistant & NLP

⚠️ More basic AI features in Power BI - full access in the expensive Fabric subscriptions

Machine Learning and Predictive Analytics 

✔️ Embedded AutoML and predictive analytics

⚠️ ML requires Fabric AutoML, consumes Fabric capacity

Comprehensive Platform

✔️ Intuitive for all skill levels with a single data pipeline, analytics engine, and AI

⚠️ Getting beyond basic operations becomes complex and requires more products

Actionable Alerting  

✔️ Data-driven alerts monitored through email, web, and mobile; triggering downstream actions

⚠️ Basic KPI altering; need Fabric and Power automate to handle complexity and scale

Governed Self-Service 

✔️ Robust governance with centralized control

❌ Less centralized governance

Mobile BI Support

⚠️ Basic mobile capabilities; mobile-specific layouts must be created and attached

Scalability 

✔️ Enterprise-ready without additional cost or products

⚠️ Requires upgrading to Fabric to scale

Embedded Analytics 

✔️ Advanced embedding into applications

✔️ Incomplete SDKs limit embedding, not self service

Combining Data Sources 

✔️ Robust native connectors and data combining

✔️ Strong within Microsoft ecosystem

Platform Architecture 

✔️ Total freedom for cloud or on-premise environments

⚠️ Restricted to Azure cloud or very limited on-premise capabilities 

Data Literacy Support

Self-paced or instructor led training programs

⚠️ Limited self-service training only 

Data Visualization

Lots of tools can make impressive-looking visualizations, but visuals should also be meaningful. Your BI tool should let you explore all your data in any direction, directly from within the visualization. That way, you can uncover relationships that you may not have considered when you or an analyst first set up a query. Plus, modern tools offer AI to help you create charts, highlight outliers, and suggest new visuals.

Laptop showing  data visualization data dashboard

Qlik Cloud Analytics

Qlik offers over 30 beautiful, highly interactive visualizations that automatically summarize, highlight patterns, and pinpoint outliers. Advanced features – such as mini-charts that profile data shape, and lasso and axis-range selectors – make your work faster and clearer. Once created, visualizations can be deployed anywhere with native mobile charts and responsive design. 

Power BI

Like many top-name tools, Power BI offers a full range of data visualizations. However, your filtering and exploration will be restricted by the predefined paths that were authored for you. Plus, if you want to view your visualizations on different screen sizes, like mobile, you’ll need to build different versions because in Power BI, they are created for a fixed screen size. 


“Not only was the Qlik platform substantially more user-friendly, but we found the visualization possibilities to be highly dynamic.”

- Sravani Nyayapathy*

Interactive Dashboards

Lots of tools can make cool-looking dashboards.  But like visualizations, you’ll need to freely explore all your data, in any direction, directly from within the analytical dashboard.

Qlik Cloud Analytics

Qlik's unique analytics engine is purpose-built for interactive, free-form exploration, allowing business users to explore and make discoveries without having to author content. AI- and ML-powered dashboards are even more powerful with added automated insight generation and natural language interaction. And when you want to move information and insights from dashboards to reports, Qlik offers robust on-demand reporting capabilities with common export formats, Tabular Reporting for structured data, or PixelPerfect for precise control over layout and appearance.  

Power BI

Power BI’s SQL engine forces you to follow specific paths and uses limited data. This means that for each query, only a slice of your data is analyzed, so patterns and connections may often go undiscovered. The only interactivity you’ll have is whatever was explicitly defined by the author. When it comes to reporting, Power BI offers instant self-service reporting and subscriptions.


“The third advantage of Qlik Cloud Analytics is its Associative Engine. This ability to quickly explore potential correlations between separate data pools is a powerful way to discover new insights.”
- Brad Ringen*

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Total Cost of Ownership

There's more to making a BI platform investment than the initial purchase price. The Total Cost of Ownership (TCO) factors in all the costs associated with using a BI solution, from implementation to usability and scalability over the years. Major cost considerations include infrastructure, systems set up, app development, cloud computing cost management, security, usability, systems admin, and support. 

A line graph showing the total cost of ownership between Qlik Sense and Power BI over a 3-year period

Qlik Cloud Analytics

Qlik has transparent predictable, capacity-based pricing. Plus, all features — like alerting, reporting, automations, and AutoML — are included with Qlik Cloud Analytics. 

Power BI

Power BI may seem low-cost on the surface. But as you add more users or need to do more complex analysis, Power BI becomes more expensive and more unpredictable compared to Qlik. Power BI at scale isn’t just Power BI, it’s Fabric and a lot of added-on features that can quickly consume capacity.


“The price comparison is very misleading.”
- Tomasz Wojcik, Thermoplast*

Augmented Analytics

Artificial intelligence (AI) and machine learning (ML) are resetting the expectations of a modern BI tool. Augmented analytics suggests new insights and connections to help you quickly analyze your data, increase your productivity, and make better data-driven decisions.

Qlik Cloud Analytics

With AI and ML integrated into its platform at a foundational level, Qlik supports a full range of augmented analytics capabilities. Insight Advisor is an intelligent AI assistant that supports automated insight generation, natural language analytics, and AI assistance. Together, these capabilities offer deeper insight, help more users become data literate, and speed time to value. 

Power BI

Simple AI use cases – can be accessed with Power BI. When complexity grows, it will require other products – Copilot Studio or Azure ML. Copilot provides a chat bot experience and authoring assistant while Quick Insights and Q&A support natural language capabilities.


“Conversational analytics in Qlik Sense allows us to give the intelligence that people in the field need right where and when they need it.”

- Pavan Arora*

Machine Learning and Predictive Analytics

Machine learning is the process of creating models from historical data in order to make future predictions. Automated machine learning allows you to use the power of predictive analytics in more cases that cannot be handled by data scientists due to labor availability, time constraints, or associated added cost.

Qlik Cloud Analytics

Qlik AutoML® allows business users to easily create ML models and generate predictive analytics, helping you move from historical analysis to next-level predictive and prescriptive analytics. With full explainability, you can understand not just what might happen, but why — so you can take action. Qlik also works well with your existing data science tools, using a full suite of real-time, pre-built connectors. 

Power BI

In Power BI, AutoML capabilities sufficient to match Qlik's built in ML/Predictive abilities can only be accessed through Premium with costly Fabric credit usage. In addition. Power BI doesn’t have nearly as many connectors as Qlik. Keeping it to business as usual, Microsoft works well only if you have their whole stack. 


“We were stumbling blind trying to figure out what would stop churn, and it was frustrating trying to find something that would move the needle. Now, machine learning has really given us direct clarity as to what will make a difference. Instead of guessing, we now know what will bring results. ”

- Ben Dean*

Comprehensive Platform

Your organization should be able to support all BI use cases using the same data and the same platform. However, this can often be challenging to accomplish. You may have many different types of users — such as analysts, engineers, and business people — with many different levels of data literacy. Each group is performing many different use cases beyond just visualizing data, such as embedding analytics, enterprise alerting, and collaborating on dashboards. How do you get everyone on the same page?

Diagram depicting Qlik Sense at the center of different use cases

Qlik Cloud Analytics

Users of all skill levels across your business can engage in the best way for them, from data exploration to real-time analytics and natural language interaction, on the same platform with a common analytics data pipeline, analytics engine, and AI capabilities.

Power BI

Power BI at its core is focused on more basic use cases (“Excel on steroids” is a common descriptor), not the full capabilities of a modern BI tool. Investing in Fabric and other tools like Power Automate would be necessary to compete with Qlik’s offering.


“Not only has Qlik's partnership brought us where we are today, but it's been used for dozens of different use cases around our organization. ”

- Jason Ferriggi*

Triggering Action

It’s not enough to create interesting dashboards and pretty visualizations — the entire point of analytics is to generate actionable insights. A complete platform must have the ability to initiate action. This can take the form of prompting human action through sophisticated alerting or automatically orchestrating events in downstream systems. 

Qlik Cloud Analytics

Qlik offers intelligent, fully data-driven alerting that is independent of any particular visualizations — delivered through email and mobile push notifications. With application automation, you can easily orchestrate worry-free events and actions in all kinds of downstream systems and workflows. 

Power BI

Power BI does support basic alerting in its standard offering but limits you to a subscription based on a single KPI. To match Qlik’s capabilities, you’ll need to buy Power Automate, a separate product that is not simple for business users to configure. 


“We believe the combination of self-alerting and mobility is responsible for the continual growth in our user base.”

- Rob O'Neill*

Governed Self-Service

To truly generate value, everyone in your organization must be able to trust their data, analytics, and insights. You also want everyone to work quickly without having to wait for often-backlogged IT or analysts. This requires a tool that allows you to control your data and content with a centralized management capability using rules-based governance without restricting what users can accomplish. 

Qlik Cloud Analytics

Qlik centralizes and unifies your data and analytics in the cloud, creating governed data models with robust data security. Because all content creation happens in the cloud, it’s governed and controlled at every step. After their initial creation, these governed libraries provide reuse and standardization for analytics. 

Power BI

Power BI takes a decentralized approach, spreading data across people’s desktops and the cloud. End users don’t have the ability to create their own viz or make changes to existing ones; they are always dependent on the authors. This makes managing data expensive, disjointed, and time-consuming. 

“Not everyone is a data geek. Creating a simple-to-use application gives everyone—regardless of their comfort with data—the tools they need to better perform their job.”
- Michael Taylor*

Mobile BI

As workforces become more mobile, keep in mind that you and your teams need to be able to explore and analyze data, then share insights whenever and wherever you happen to be. 

Image of a mobile phone showing a Qlik Sense dashboard metric and chart

Qlik Cloud Analytics

Qlik offers a fully native mobile app — its analytics engine runs locally and alerts are pushed. With responsive design and touch interaction native to the Qlik platform, you get fully interactive online and offline exploration plus integrated alerting without having to redesign apps for mobile access. 

Power BI

Power BI has a view-only mobile app with limited alerting. Because they aren’t responsive, reports must have an attached, mobile-optimized layout for best results.

Scalability

You need a complete, up-to-date view of all relevant data. Plus, you may need to support hundreds or thousands of users across your organization. This means you’ll need a tool that can handle data at any scale without compromising performance or driving up costs. It must also be able to integrate and combine data from any source, as close to real time as possible.

Qlik Cloud Analytics

Qlik’s associative engine provides instant calculation performance even with massive datasets, real-time data unanticipated questions, and high numbers of users. With Qlik's robust incremental update and partial reload features, you can keep data fresher in a much smaller build window. Learn more.

BONUS: On Qlik, whether 1 or 50,000, the same software is used to deploy any use case.

Power BI

Microsoft makes you pay extra if you want to scale. Once you pass Power BI Pro’s low data limit of 1GB per dataset, you have to upgrade to Premium with Fabric (or use live query, which will slow everyone’s work to a crawl). Even when Microsoft works with big volumes it will always come with a much higher cost or much lower performance. Also, don’t be fooled by the cheap Pro license offered by Microsoft. To get all the capabilities, you can’t buy just one Pro license — as you scale Power BI, you must add products. 


“Near the beginning of our journey with the analytics platform Qlik, we had about 2,000 users. However, as word spread, the number of interested staff grew exponentially. Roughly a year later, in 2020, we had nearly 20,000 users on the platform. As of the first quarter of 2021, more than 35,000 people were engaged.
- Axel Goris*

Embedded Analytics

Embedded analytics refers to incorporating full analytics capabilities within other applications, processes, and portals across an organization. It lets your employees, partners, suppliers, and customers make better, data-driven decisions from within the systems they already use.

Qlik Cloud Analytics

Qlik’s platform was built API-first using modern standards. This means you can embed a dashboard — and individual numbers, values, and metrics — within the latest web and application technologies. 

Power BI

While Power BI does make it possible to embed dashboards and objects within other apps, Power BI is not API-first. Many capabilities are not available in its SDKs, the more relevant being the lack of self-service. 


“Qlik’s complete set of open APIs enables us to fully customize analytics solutions, rapidly develop new custom apps, visualizations, and extensions, and embed fully interactive analytics within the applications people use every day.

- Aaron Growitz*

Combining Data Sources

To get a holistic view of your business, your BI tool must be able to easily bring together data  from hundreds of data sources such as apps, databases, streaming data , and cloud services. Robust data prep and combination capabilities are essential for applications that go beyond just a single source. They must also not be limited by the complexities of SQL.

Qlik Cloud Analytics

Qlik’s associative engine is the key to combining many different types of data from many different sources, at scale, without the limitations of SQL-joins. With both graphical data transformation and powerful scripting, you can easily deal with even the most complex of data preparation challenges. 

Power BI

Making data integration work in Power BI requires you to purchase additional products from the Microsoft stack. You can have good performance with One Lake (part of Microsoft Fabric) but now you’re required to pay additional capacity and storage fees for One Lake. Even then, it can still be difficult to manage the disparate offerings, not to mention additional platforms for data prep. 


“Databases can be huge, with information coming from multiple sources. Qlik’s associative selection model and powerful data engine make it simple to turn piles of data into wisdom.”

- Sandra Norman Andersen*

Platform Architecture

You shouldn’t be limited in your cloud strategy or by where your data resides. Your BI tool should have a platform-agnostic, multi-cloud architecture that avoids vendor lockin and lets you deploy in any environment, from on premises to cloud to hybrid. 

Qlik Cloud Analytics

As an independent platform, Qlik offers you total freedom and control for your data, whether it resides in one or more cloud environments or on premises. Qlik provides a full enterprise SaaS environment and on-premises or private cloud deployment options Learn about Qlik Cloud.

Power BI

Data Literacy Support

Most vendors will teach you how to use their tool. Today, you need more. You need people at all levels of your organization to be data literate beyond just the tool they use. They must be able to ask the right questions of data and machines, make data-driven decisions, and communicate insights and meaning to others. 

Qlik Cloud Analytics

Qlik makes it easy for anyone, at any skill level, to explore their data. Even better, Qlik offers data literacy training programs for any user. Users are able to make copies of projects, experiment and explore on their own for a truly collaborative experience. 

Power BI

Power BI only provides self-service access to authors. Once those authors have published content, it’s only available with very limited interactivity. All other users must go back to the author for a new report when they want to explore deeper. 


“We use features like Qlik Continuous Classroom to help people to develop data literacy.”

- Vladimir Baklanov*

*Qlik User Survey

Should you compare QlikView vs Power BI?

We’re flattered by the legacy usage, but definitely not. QlikView® was Qlik’s first product introduced over 30 years ago, igniting the data discovery revolution. Many customers still use and love QlikView and while Qlik continues to support them, Qlik Cloud Analytics is the lead analytics solution — learn more about the differences here

When Power BI compares itself to Qlik, they focus on QlikView. While it’s understandable why they would do this (Windows 11 sure looks great next to Windows 95), it’s actually quite misleading, as they’re not comparing themselves to the modern platform, Qlik Cloud Analytics.

The resulting misinformation can cause confusion and delays for conscientious buyers trying to perform their due diligence. 

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