Many tools can create beautiful visualizations. However, your BI tool should allow you to explore all your data in any direction directly from the visualization. This way, you can discover relationships that you may not have considered when you or an analyst first created a query. Modern tools also offer AI to help you create charts, highlight anomalies, and suggest new visualizations.
Qlik Sense: Qlik offers over 30 beautiful, fully responsive visualizations that automatically summarize the data structure, highlight patterns, and identify anomalies. The associative engine running in the background drives advanced geographic calculations and AI/ML, providing an interactive experience and powerful insights.
Power BI: Like most top tools, Power BI offers a wide range of data visualizations. However, your filtering and exploration will be limited by predefined query paths. Additionally, if you want to view visualizations on different screen sizes, such as mobile, you will need to create different versions, as visualizations are designed for a fixed screen size.
Many tools can create beautiful dashboards. However, just like with visualizations, you need to be able to explore all your data freely, in any direction, directly from the analytical dashboard.
Qlik Sense: Qlik's unique analytics engine is specifically designed for interactive, free-form exploration, allowing business users to explore and discover new insights without needing to create content. AI and ML make dashboards even more powerful by adding automated insight generation and interaction via natural language.
Power BI: Power BI's SQL engine forces you to follow specific paths and limits you to a restricted dataset. This means that for each query, only a portion of your data is analyzed, allowing patterns and connections to go unnoticed. Aside from Power BI's Q&A feature, the only interactivity is that which is explicitly defined by the author.
There is more to investing in a BI platform than just the initial purchase price. Total Cost of Ownership (TCO) takes into account all the costs associated with using a BI solution, from implementation to usability and scalability over the years. Key cost factors include infrastructure, system setup, app development, cloud computing cost management, security, usability, system administration, and support.
Qlik Sense: Qlik has no additional or hidden costs when you scale. Additionally, all features—such as alerts and AutoML—are included in Qlik, while you have to add each individual feature as an extra cost with Power BI.
Power BI: Power BI may seem cheap on the surface. However, when you add more users or want to perform more complex analyses, Power BI becomes more expensive than Qlik.
Artificial intelligence (AI) and machine learning (ML) are changing expectations for modern BI tools. Augmented analytics suggest new insights and connections, helping you quickly analyze your data, increasing your productivity, and assisting you in making better data-driven decisions.
Qlik Sense: With AI and ML integrated into its platform at a fundamental level, Qlik supports a complete range of augmented analytics capabilities. Insight Advisor is an intelligent AI assistant that supports automated insight generation, natural language understanding, and AI assistance. These features provide deeper insights, help more people become data literate, and increase the speed of realizing value.
Power BI: A few Microsoft AI features are accessible through Power BI. Co-Pilot provides a chatbot experience and assistance with content creation. Quick Insights and Q&A support natural language features. However, these two NL features are objects on a dashboard that you need to add each time.
Machine learning is the process of creating models based on historical data to make predictions about the future. Automated machine learning allows you to harness the power of predictive analytics in multiple use cases that are typically not handled by data scientists.
Qlik Sense: Qlik AutoML makes it easy for business users to create ML models and generate predictive analytics, helping you move from historical analysis to predictive and prescriptive analysis. With full transparency, you can understand not only what might happen but also why, enabling you to take action. Qlik also works well with your existing data science tools by using a complete set of real-time connections.
Power BI: Power BI's AutoML features require Azure ML, a separate product designed for data scientists and experts, which incurs additional costs. Additionally, Power BI has far fewer connections than Qlik. As usual, Microsoft works best if you are already using their entire product suite.
Your organization should be able to support all BI use cases using the same data and the same platform. This is because you can have many different types of users, such as analysts, engineers, and business professionals, performing a variety of tasks beyond just visualizing data—such as embedding analytics, business alerts, and collaborating on dashboards.
Qlik Sense: Users at all skill levels in your organization can engage in the way that suits them best, from data exploration to real-time analysis and interaction with natural language, all on the same platform with a shared analytics pipeline, analytics engine, and AI capabilities.
Power BI: Power BI covers a range of common use cases, but you need to invest in the entire Microsoft data and analytics suite to get the full benefit. Power BI is fundamentally focused on more basic use cases ("Excel on steroids") and does not offer the full capabilities of a modern BI tool.
It is not enough to create dashboards and visualizations. Your platform should have the ability to initiate action. This can be in the form of promoting human action through sophisticated alerts or orchestrating events in downstream systems.
Qlik Sense: Qlik offers intelligent, fully data-driven alerts that are independent of specific visualizations and are delivered via email and mobile push notifications. With application automation, you can also orchestrate events and actions in all types of downstream systems and workflows.
Power BI: Power BI supports basic alerts in the standard version but limits you to a subscription service based on a single KPI. To match Qlik's capabilities, you need to purchase Power Automate, a separate product that is not easy for business users to configure.
You want everyone in your organization to be able to trust their data, analyses, and insights. You also want everyone to be able to work quickly without waiting for IT or analysts. This means your tool should allow you to manage your data and content with a centralized governance capability that uses rule-based governance without restricting what users can achieve.
Qlik Sense: Qlik centralizes and consolidates your data and analytics in the cloud, creating governed data models with robust data security. All content creation occurs in the cloud, where it is managed and controlled at every step. Additionally, governed libraries enable reuse and standardization of analyses.
Power BI: Power BI takes a decentralized approach, where data is scattered across users' desktops and in the cloud. End users do not have the ability to create their own visualizations or modify existing ones; they are always dependent on authors. This makes data governance expensive and time-consuming.
As the workforce becomes more mobile, you need to ensure that you and your teams can explore and analyze data and share insights, regardless of where you are.
Qlik Sense: Qlik offers a fully integrated mobile app with its analytics engine running locally and push notifications. With responsive design and touch interaction built into the Qlik platform, you get fully interactive online and offline exploration as well as integrated alerts without needing to redesign apps for mobile access.
Power BI: Power BI has a mobile app, but it only allows viewing, not creation, and offers limited alert functionality. Additionally, reports are only responsive if they are built for display on mobile devices.
You need a complete and up-to-date overview of all relevant data. Additionally, it may be necessary to support hundreds or thousands of users across your organization. This means you need a tool that can handle data at any scale without compromising performance or increasing costs, and that can integrate and combine data from any source as close to real-time as possible.
Qlik Sense: Qlik's associative engine delivers instant calculation performance, even with massive datasets, real-time data, unexpected queries, and a large number of users. With Qlik's robust features for incremental updates and partial reloads, you can keep your data fresh in a much smaller update window.
Power BI: Microsoft will charge you extra if you want to scale. When you exceed Power BI Pro's low data limit of 1 GB per dataset, you must upgrade to Premium (or use live queries, which will slow everyone's work). Even when Microsoft works with large data volumes, it will always come with either much higher costs or much lower performance.
To gain a holistic overview of your business, your BI tool should easily be able to gather data from hundreds of data sources such as apps, databases, streaming data, and cloud services. Strong data preparation and combination features are essential for applications that extend beyond just a single source. They should not be limited by the complexities of SQL.
Qlik Sense: Qlik's associative engine is key to combining many different types of data from various sources at scale, without the limitations of SQL joins. With both graphical data transformation and powerful scripting, you can handle even the most complex data preparation challenges.
Power BI: To get data integration to work in Power BI, you need to purchase additional products from the Microsoft suite. You can achieve good performance with One Lake (part of Microsoft Fabric), but you will incur extra capacity and storage fees for One Lake. Even then, it can be challenging to manage the various offerings.
You should not be limited in your cloud strategy or where your data resides. Your BI tool should have a platform-agnostic, multi-cloud architecture that allows you to implement in any environment, from on-premise to cloud to hybrid.
Qlik Sense: As an independent platform, Qlik provides you with full freedom and control over your data, whether it resides in one or multiple cloud environments or on-premise. Qlik offers a fully enterprise SaaS environment as well as on-premise or private cloud implementation options.
Power BI: With Power BI, you are locked into Azure. There is no hybrid option, and if you want to host on-premise, you must use a very limited version of Power BI.
You should not be limited in your cloud strategy or where your data resides. Your BI tool should have a platform-agnostic, multi-cloud architecture that allows you to implement in any environment, from on-premise to cloud to hybrid.
Qlik Sense: As an independent platform, Qlik provides you with full freedom and control over your data, whether it resides in one or multiple cloud environments or on-premise. Qlik offers a fully enterprise SaaS environment as well as on-premise or private cloud implementation options.
Power BI: With Power BI, you are locked into Azure. There is no hybrid option, and if you want to host on-premise, you must use a very limited version of Power BI.
Most vendors will teach you how to use their tool. Today, you need more. You need people at all levels in your organization to be data literate. They should be able to ask the right questions of data and machines, make data-driven decisions, and communicate the meaning to others.
Qlik Sense: Qlik makes it easy for everyone, regardless of skill level, to explore their data. Additionally, Qlik offers data literacy training programs for all users. This creates a more collaborative experience where users can make copies of projects and experiment and explore on their own.
Power BI: Power BI only provides self-service access to authors. Once these authors have published content, it is only available with very limited interactivity. All other users must go to the author to get a new report if they want to explore the data further.
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