Qlik to Power BI Migration: A Comprehensive Guide

Qlik and Microsoft Power BI are well-established leaders in the business intelligence (BI) and data analytics space, enabling organizations to transform raw data into actionable insights. While both platforms deliver strong capabilities across data integration, modeling, and visualization, a growing number of organizations are strategically transitioning their BI environments from Qlik to Power BI. 

This guide is designed to support organizations currently leveraging Qlik by outlining the key drivers behind this shift, the operational and technical considerations involved, and a structured roadmap for a successful migration. Whether driven by cost efficiency, platform standardization, or integration with broader Microsoft ecosystems, this resource will help decision-makers evaluate the move and plan with confidence.  

Here is a quick outline for the guide: 

1. Key reasons why enterprises look to migrate from Qlik to Power BI 
2. Factors enterprises must consider while migrating to Power BI
3. Qlik vs Power BI: A comparison of visualizations
4. Qlik vs Power BI: A comparison of generic Capabilities
5. Leveraging third party visuals in Power BI
6. A note for enterprises using VizLib extensions for Qlik
7. Key recommendations for planning & executing Qlik to Power BI migration
8. Summary 

Organizations contemplating a move from Qlik to Power BI are often driven by a set of key factors that align with their strategic objectives and operational needs. Let’s look at a few of them. 

1. Cost-Effectiveness and Licensing Benefits

   A significant driver for many organizations considering a migration to Power BI is the potential for cost savings and the advantageous licensing model it offers.  Power BI frequently emerges as a more cost-effective solution, particularly for enterprises that have already invested in the Microsoft ecosystem. The financial advantage is often amplified by the fact that Power BI Pro licenses may be included with existing Microsoft 365 subscriptions, allowing organizations to leverage their current investments.   Organizations transitioning to Power BI have noticed a substantial reductions in licensing costs, with potential savings. This considerable decrease in expenditure can have a direct and positive impact on an organization's return on investment in data analytics.

2. Seamless Integration with the Microsoft Ecosystem

   Power BI offers seamless integration with a wide array of Microsoft products, including Office 365, Azure, and SQL Server. This deep level of integration streamlines data workflows, fosters enhanced collaboration across teams, and allows organizations to capitalize on their existing Microsoft infrastructure.  For companies already heavily invested in Microsoft technologies, Power BI presents a natural and efficient extension of their current technology stack, simplifying data management, sharing, and the embedding of reports within familiar Microsoft environments. 

3. Comprehensive Data Management with Microsoft Fabric

   Microsoft Fabric represents a significant evolution in Microsoft's data and analytics offering, providing a unified platform that integrates various data services, including data engineering, data science, real-time analytics, and business intelligence through Power BI. This integration offers numerous advantages for organizations, including seamless data integration from a multitude of sources, enhanced data governance and security through a centralized environment, real-time data processing capabilities for timely insights, and highly scalable data management solutions designed to handle even big data scenarios.  By providing a more cohesive and efficient data ecosystem, Fabric simplifies the complexities often associated with managing distributed data environments, making Power BI an even more compelling choice for organizations seeking a modern and integrated data analytics platform.

4. Investments in Microsoft AI and Machine Learning ecosystem

   Power BI and Qlik both offer robust AI and ML capabilities, though their approaches and strengths differ.  Power BI tightly integrates with the Microsoft Azure ecosystem, providing seamless access to Azure Machine Learning, Azure AI services, and built-in features like anomaly detection and key influencers.   Qlik offers its own comprehensive AI/ML suite, including Qlik AutoML, Insight Advisor, and Associative AI, emphasizing automated model building and leveraging its associative engine for unique insights.   While Qlik provides strong native AI/ML, organizations deeply invested in the Microsoft ecosystem might find Power BI's integrated access to Azure's advanced AI/ML services a compelling reason to migrate, potentially streamlining workflows and leveraging existing cloud infrastructure for more specialized AI/ML applications beyond standard BI tasks. 

5. User-Friendly Interface and Faster Adoption

   Power BI is designed with an intuitive and user-friendly interface, which can significantly reduce the learning curve for users. This ease of use promotes faster adoption across the organization and empowers a broader range of employees to engage with data effectively, fostering a stronger data-driven culture. By making data accessible to a wider audience, organizations can democratize insights and accelerate the decision-making process.

Migrating from Qlik to Power BI is a significant undertaking that requires careful planning and consideration of various factors to ensure a smooth and successful transition. 

1. Compatibility and Migration of Data Sources

   A fundamental step involves assessing the compatibility of existing Qlik data sources with Power BI. While both platforms support a wide variety of data sources, organizations need to verify the availability of specific connectors and understand potential differences in how data is handled and transformed. This might necessitate exploring alternative connection methods or implementing additional data preparation steps within Power BI.

2. Complexity and Effort Required for Application Reconstruction

   The complexity of existing Qlik applications, including their data models, calculations, and visualizations, must be carefully evaluated. Migrating intricate Qlik applications can be a substantial undertaking, potentially requiring the translation of Qlik's proprietary scripting language and data modeling logic into Power BI's DAX language and relational data model. Understanding this complexity is crucial for accurately estimating the migration effort, establishing a realistic timeline, and allocating the necessary resources.
   

3. Differences in Data Modeling and the Transition to DAX

   Organizations must also understand the fundamental differences in data modeling paradigms between Qlik and Power BI. Power BI often emphasizes a relational star schema design, which might necessitate restructuring data from Qlik's associative data model. Proper data modelling in Power BI is critical that can adopt to Qlik’s Unrestricted, dynamic, context-sensitive data exploration methods. While migration scripting techniques should also be considered where Qlik supports an advanced scripting on load, Power BI used Power query (M) and DAX for transformation. 

4. User Training and Change Management

   Planning for comprehensive user training on Power BI is essential, as users accustomed to Qlik's interface will need to adapt to the distinct look and feel of Power BI. Effective change management strategies and well-structured training programs are vital for ensuring a seamless transition and maximizing user adoption of the new platform. Investing in training will empower users to confidently leverage Power BI's features and minimize disruptions to their analytical workflows.
   

5. Data Governance and Security in the New Environment

   Establishing a robust data governance framework for Power BI is paramount to ensure data quality, security, and compliance.1 While Power BI offers a suite of data governance features, organizations must define and implement appropriate policies and procedures to effectively manage data within the new environment. A well-defined governance framework will build trust in the accuracy and reliability of the insights generated from Power BI.
   

6. Testing and Validation Procedures

   Thorough testing and validation of the migrated data and reports within Power BI are crucial to guarantee accuracy and consistency with the original Qlik applications. Implementing data validation checks and generating comparison reports can help identify any discrepancies that may arise during the migration. Rigorous testing will build confidence in the reliability of the migrated data and reports, minimizing the risk of errors and ensuring business continuity.
   

7. Timeline and Resource Allocation

   Developing a realistic timeline for the entire migration project is essential, taking into account the complexity of the Qlik applications and the availability of skilled resources with expertise in both Qlik and Power BI. Migrating a substantial number of intricate applications can be a significant undertaking, demanding careful planning and the allocation of adequate resources to ensure the project stays on schedule and within budget

Power BI offers a wide array of native visualizations that cater to most common business reporting needs. However, its capabilities can be significantly extended through the integration of third-party custom visuals available in the Power BI marketplace. Tools like Inforiver, in particular, can provide advanced charting options and features that bridge the gap with Qlik's visualization library. The subsequent section on leveraging third-party visuals delves deeper into this aspect. 

The following table provides a comparison of the availability and key features of various visualization types in Qlik and Power BI: 

While both platforms offer a comprehensive set of visualizations, Qlik is often recognized for its associative data model enabling unique data exploration, whereas Power BI's capabilities are continuously expanding, and its growing library of custom visuals provides a powerful way to bridge any remaining gaps. 

Beyond the specific chart types, organizations also need to consider the broader generic capabilities offered by Qlik and Power BI when evaluating a migration.  

The following table provides a comparative overview of some key features: 

While both tools offer a robust set of generic capabilities, Qlik's associative engine provides a unique approach to data exploration, whereas Power BI stands out for its seamless integration within the Microsoft ecosystem and a generally more user-friendly approach for many common tasks. 

Power BI's native visualization capabilities, while extensive, can be further enhanced through the use of custom visuals available in the Power BI marketplace. These third-party visuals can provide advanced charting options and features that might not be available in the standard library, often bridging the gap with tools like Qlik. 

Inforiver is a suite of custom visuals for Power BI that significantly expands its reporting and analytics functionalities. These visuals offer a no-code environment for creating a wide range of advanced charts, tables, and KPI cards, often replicating or even surpassing features found in Qlik. 

• Bar/Column Charts: Inforiver provides integrated variance analysis, allowing for direct comparison against previous periods, targets, or budgets within the chart itself. It also offers split bar charts for visualizing part-to-whole relationships with additional context. 

• Pie/Donut Charts: Inforiver offers enhanced customization options for pie and donut charts, including control over angles, shapes (semi-circle/circle), orientation, and the ability to add images. 

• Tables (Crosstabs): Inforiver Reporting Matrix excels in creating advanced matrix reports with features like row and column hierarchy support (expand/collapse), cell-level formatting, custom row and column grouping/reordering, annotations, Excel-like formulae, and formatted exports to Excel/PDF. It also supports paginated reports with features like first-previous-next-last navigation and custom page/section breaks. 

• Treemaps/Sunburst: Inforiver Analytics+ includes hierarchical charts like treemaps and sunburst charts for visualizing hierarchical data with various customization options. 

• Box & Whisker Plots: Inforiver supports box and whisker plots with the ability to handle both dynamic and pre-calculated quartiles, offering more flexibility than standard Power BI visuals. 

• Bullet Charts: Inforiver Analytics+ provides multiple variations of bullet charts, including IBCS-compliant options, comparative bullets, and multi-measure bullet charts, offering more flexibility than native Power BI. 

• Gantt Charts: Inforiver integrates with xViz Gantt, providing a best-in-class Gantt chart for Power BI with features like multi-level timelines, dependencies, resource allocation, and progress tracking. 

• Waterfall Charts: Inforiver Analytics+ offers over 20 advanced waterfall chart types, including measure-based interim, stacked, and dual breakdown waterfalls, as well as variance and combination waterfalls. 

• Funnel Charts: Inforiver provides executive funnel charts for tracking cumulative conversion and drop-off ratios at each stage of a process. 

• Pareto Charts: Inforiver Analytics+ supports Pareto analysis for identifying the most significant factors contributing to an outcome. 

• Sparklines: Inforiver supports embedding sparklines across all chart types, allowing for trend visualization within various contexts. 

• Small Multiples: Inforiver offers comprehensive support for creating small multiples or trellis layouts for all chart types and KPI cards, similar to the capabilities in Qlik. It also allows for splitting and grouping measures into trellis panels like Tableau. 

• Radar/Polar Charts: Inforiver Analytics+ includes radar/polar charts for visualizing multi-dimensional data. 

• Sankey Diagrams: Inforiver Analytics+ supports Sankey charts for visualizing flows and distributions between different categories. It is part of special chart group. 

• Network Diagrams: Inforiver integrates with xViz Performance Flow to enable the creation of interactive process, hierarchy, and network diagrams with integrated KPIs and alerts. 

• Heatmaps: Inforiver allows for the creation of heatmaps within tables using conditional formatting rules. 

• Org Trees: Inforiver integrates with xViz Performance Flow to provide features for building interactive organization charts with performance indicators and trends. 

• Motion Chart: Inforiver Analytics+ offers play axis feature within storyboard. This allows to use play/pause action to animate chart over time. 

• Marimekko Charts: Inforiver Marimekko allows you to plot categorical data across two dimensions where height and width both vary. It has stacked and 100% variations. 

• Packed Bubbles: Easily plot cluster of data varying by size with Inforiver. This is included in Hierarchy family which allows clustering and grouping with Packed bubbles. 

• Parallel Coordinates: Inforiver special chart group enables to plot multiple variables across categories for comparison. This can be built in very easy steps. 

• Butterfly Chart: Inforiver Analytics+ tornado chart can be used to compare two measures across multiple categories. They can be plotted on a shared axis or two separate axes. This is part of Inforiver special chart group. 

• Histogram: Inforiver supports statistical chart including histogram for plotting data bins with distribution curves. 

• Dot Plot: Inforiver Analytics+ offers are the popular storytelling charts including dot plot, arrow plot, range bar and more to build effective visualization. 

• Slope Graph: Inforiver provides slope graph to plot ranking change over two points of time by grouping measures. It comes with dynamic top/bottom N colour. 

• Linear/Angular Gauge: Inforiver provides gauge chart to compare actual against target measure. It supports dual axis, orientation support and comes with comparison band formatting. 

• xViz Gantt: Advanced Project Management and Timeline Visualization 
  xViz Gantt is a custom visual for Power BI that provides advanced capabilities for project management and timeline visualization. Key features include the ability to display baseline bars for comparing planned vs. actual timelines, track project progress visually, define customizable connector lines to visualize task dependencies, create multi-level timelines for detailed project tracking, offer interactive timeline zooming, apply conditional formatting to highlight critical tasks or milestones, and incorporate reference lines and ranges to indicate key project deadlines or targets. xViz Gantt also supports custom images and icons for milestones, custom date/time formats in timeline headers, tooltips on milestones, and the ability to show conditional formatting rules in the legend. 

• Performance Flow: Building Interactive Process, Hierarchy, and Network Diagrams 
  xViz Performance Flow is a custom visual designed for building interactive process, hierarchy, and network diagrams within Power BI. It supports various use cases, including the creation of organization charts with integrated alerts and KPIs, visualization of supply chain performance across different locations, building network diagrams to track the performance of business units or departments, and visualizing sales and financial performance across various dimensions. Key features include the ability to use images and icons for enhanced visualization, integrate alerts and KPIs to highlight performance against benchmarks, draw custom connectors and swim lanes to represent process flows, add notes for providing additional context, highlight shapes based on performance rules, and deliver interactive diagrams with expand/collapse levels, dynamic filtering, quick search, and zoom capabilities. 

Some organizations that use Qlik have invested heavily in extensions like Vizlib. If you are considering migrating from Qlik Sense to Power BI, a key consideration is ensuring that the advanced capabilities provided by Vizlib can be matched in Power BI. 

This is where Inforiver Analytics+, Reporting Matrix and Super Filter for Power BI become a significant enabler and a major determinant for migration. These visuals comprise 100+ charts, KPI cards, tables, matrices, and filters, providing an all-in-one solution for advanced reporting within the Power BI ecosystem. 

Comparable features offered by Inforiver to those Vizlib provides in Qlik are as follows: 

• Extensive Chart Library: Similar to Vizlib's specialized charts, Inforiver offers a wide array of advanced and specialized visuals. This includes multi-level Waterfalls, Marimekko, Statistical charts like Box Plot & Histograms, Gauge, hierarchy charts like Treemaps and Packed Bubble, combo/multi-axes charts, Funnel, Pyramid, Radar/Polar, multi-measure Bullet charts, and special charts like Sankey, Lollipop, Slope, Parallel Coordinates, Dumbbells, Ribbons, and Tornado charts, along with integrated Gantt charts (like xViz Gantt). This extensive library reduces the need for multiple custom visuals. 

• Advanced Tables & Matrices: Inforiver provides highly flexible matrix visuals with granular cell-level formatting, hierarchy management, financial reporting fonts, pagination, layouts, templates, in-visual calculations, what-if simulations, forecasting, commenting, and collaboration capabilities. Inforiver offers greater data density compared to Vizlib's advanced table capabilities, which is crucial for detailed reporting. 

• Rich Filtering Experiences: SuperFilter is a free, all-in-one filter for Power BI that combines date filtering, a filter panel using facet filtering, hierarchy filters, and measure filtering. It simplifies complex reporting tasks and enhances user insights with features like bulk filtering, advanced search, and custom presets. Key features include a Calendar Date Filter with options like Date Slider, Calendar Date Picker, Dynamic Date Presets, and Fiscal Year Support; a Facet Filter that consolidates multiple slicers into one panel with flexible layouts and diverse selector types; Advanced Filtering with capabilities like advanced search, measure filter, and popup mode; and Dynamic Filtering with saved filters, conditional formatting, and presets. 

• Integrated Variance Analysis: Inforiver offers automated calculations of variances with one-click template options for comprehensive variance representation. 

• Comprehensive Small Multiples: Inforiver applies robust trellising across charts, tables, and KPI cards, mirroring Vizlib's advanced small multiples functionality for comparative analysis. (It's important to mention Inforiver's ability to create small multiples on any chart, including multi-dimensional & hierarchical small multiples). 

• Rich KPI Visualizations: Inforiver enables the creation of data-dense KPI cards with multiple metrics and integrated contextual visuals for a comprehensive overview. 

• Storytelling & Collaboration: Inforiver includes data point and canvas annotation features and integrated comments for data storytelling and collaboration. 

• Enhanced Exporting: Inforiver offers advanced export options to Excel and PDF that preserve formatting and layouts, addressing the need for high-quality static report generation. 

By providing a comprehensive suite of advanced reporting and visualization capabilities, Inforiver achieves feature parity for critical items such as advanced tables, specialized charts, enhanced interactivity & filtering, and detailed formatting. 

Based on the insights gathered, the following key recommendations are crucial for enterprises planning and executing a migration from Qlik to Power BI: 

1. Conduct a Thorough Assessment of Your Current Qlik Environment: Perform a comprehensive audit of all Qlik assets, including applications, dashboards, data sources, users, and usage patterns. Identify critical reports, dependencies, and redundancies to define the migration scope and prioritize efforts.  
   
   
2. Develop a Phased and Detailed Migration Plan: Create a well-defined migration plan with clear objectives, scope, timelines, and responsibilities. Start with a pilot project to test the migration process and identify potential challenges before scaling to the entire Qlik environment. 
   
   
3. Establish Robust Data Governance and Security Measures in Power BI: Implement appropriate data governance policies and configure Power BI's security features to ensure data integrity and compliance. 
   
   
4. Focus on Rebuilding and Optimizing Applications for Power BI's Architecture: Anticipate that applications and dashboards will need to be rebuilt in Power BI. Optimize data models and DAX queries for performance, taking advantage of Power BI's strengths. 
   
   
5. Implement Rigorous Testing and Validation Procedures 1: Conduct thorough testing and validation of migrated data and reports to ensure accuracy, functionality, and performance in the Power BI environment. 
   
   
6. Provide Comprehensive Training and Support to End Users: Invest in comprehensive training programs to familiarize users with Power BI's interface and features. Provide ongoing support to address user questions and challenges during the transition. 
   
   
7. Consider Utilizing Automated Migration Tools and Expert Services: Explore the availability of automated migration tools and consider engaging with expert service providers who have experience in Qlik to Power BI migrations to accelerate the process and minimize risks. 
   
   
8. Establish Post-Migration Monitoring and Feedback Mechanisms: After the migration, continuously monitor the performance and usage of Power BI reports and dashboards. Gather feedback from users to identify any issues or areas for improvement and make necessary adjustments to optimize the new environment.