How to Migrate from Qlik to Power BI: Step-by-Step Guide

What makes the Qlik to Power BI Migration Beneficial?

Migrating from Qlik to Power BI offers significant advantages, such as cost savings, integration, and analytics capabilities. The following benefits can be obtained from Power BI.

• Cost savings: Qlik’s licensing is costly, whereas Power BI licenses are generally much cheaper per user. Sometimes they might also be bundled with Microsoft 365 E5 subscriptions. Migrating to Power BI allows a better, more cost-effective solution for companies of all sizes. With its cloud-based architecture, Power BI reduces the need for expensive hardware and maintenance, allowing teams to focus resources on analytics rather than infrastructure. For businesses, this means streamlined budgeting and improved ROI on data projects.
• Integration with the Microsoft Ecosystem: Power BI is not just a standalone tool. Power BI reports can be embedded directly into the apps. This allows teams to connect data, share reports, and collaborate without moving between disconnected systems. This simplifies administration and reduces complexity.
• Advanced AI and Analytics: Power BI has integrated Copilot and AI features that generate report pages or summaries with the help of natural language processing. Their machine learning insights help in driving deeper analytics for decision-making.
• Enhanced Collaboration and adoption: Reports and dashboards in Power BI can be shared securely through the Power BI service. Power BI features are more intuitive and user-friendly than Qlik and easy to adopt. Learning curve is less compared to Qlik.
• Security and Compliance: Power BI provides centralized administration through its Admin portal. IT teams can monitor usage, manage workspaces, enforce data policies, and maintain consistent reporting standards across departments.

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Challenges faced during the Qlik to Power BI Migration and ways to overcome

Migrating from Qlik to Power BI comes with a lot of challenges and technical shifts. The key challenges are

• Data Modeling Differences: Qlik developers rely on Set Analysis to perform complex filtering within a measure. Power BI requires explicit relationships between tables. To overcome this, redesign data models using a star schema approach. Conduct model testing before publishing the results.
• Rebuilding logic: Qlik uses load scripts while Power BI relies on Power Query and DAX. Complex Qlik scripts cannot be directly imported into Power BI and need rebuilding. To overcome this, break complex logic into small parts and validate each transformation individually.
• Performance issues: Reports may experience slow refresh times after migration. This is due to inefficient data models or poorly optimized DAX measures. To overcome this, optimize data models using a star schema. Use DAX measures instead of row-level calculations.
• Security Model Differences: Implementing security is different in Power BI. It can be complex to recreate access rules in Power BI. To overcome it, recreate Row-Level Security (RLS) in Power BI using DAX. 
• User Adoption: Users familiar with Qlik may find it difficult to work in Power BI. They may expect identical dashboards and workflows in Power BI. To overcome this, provide training sessions and user guides. Collect feedback during early adoption phases. 

Best Practices for a Smooth Qlik to Power BI Migration

• Define a clear objective and create a roadmap with what needs to be done and why it is needed. They should be aligned with business goals.
• Do an audit in the Qlik environment and list down the dashboards, scripts, and data sources.
• Prioritize critical dashboards rather than a big bang migration.
• Document existing data models, transformations, and KPIs before conversion.
• Implement Row-Level security with clearly defined user roles.
• Validate data accuracy by comparing both Qlik and Power BI.
• Check the usage level of the reports and move only them.
• Train users on the Power BI interface.
• Continuously monitor it even after the migration is completed.

How to Migrate from Qlik to Power BI: Step-by-Step Process

Migrating from Qlik (Sense or View ) to Power BI is a translation of logic from a non-linear associative engine to a SQL-based relational engine. The step-by-step roadmap is discussed below.

1. AI-based Qlik environment assessment:

Before migrating from Qlik to Power BI, start by automating the discovery of your Qlik environment. 

• List all the dashboards, reports, and applications. 
• Document every data source and identify where heavy lifting happens
• Categorize the Qlik reports based on their complexity level (low, medium, high) and create a road map.

2. Define migration scope:

Check on the needs for Power BI, like why migration is needed. Power BI gives the following features: improving performance and scalability, reducing licensing costs, enabling self-service analytics, and standardizing reporting.

3. Data source and Model Migration:

Qlik uses Associative Engine, whereas Power BI uses VertiPaq Engine. Check on the data compatibility of both Qlik and Power BI. Document Qlik load scripts to understand data transformations. Before rebuilding reports, review data quality and consistency. Power BI relies on structured and optimized data models. Proper preparation ensures better performance after migration.

4. Data Transformation (ETL):

Document Qlik load scripts to understand data transformation. Recreate the Qlik data model in Power BI Desktop. Using AI tools ensures performance-ready models aligned with Power BI best practices. Rebuild data models by establishing relationships between tables. 

5. DAX Calculations:

Convert Qlik’s Set Analysis into DAX (Data Analysis Expressions). Since Qlik’s associative engine differs from Power BI, filters and selections must be rebuilt using DAX. Use AI to reduce calculation errors and improve performance tuning.

6. Rebuild Reports and Dashboards:

Now start recreating reports by mapping Qlik visualizations to equivalent Power BI visuals. Try to re-evaluate if Power BI’s native visuals offer better insights and improve the report design. Use Copilot for Power BI to generate report pages based on your semantic model. 

7. Security and Governance:

Map Qlik’s section Access to Power BI Row-Level Security (RLS). Define workspace roles and permissions. Thus, Power BI integrates with Microsoft Entra ID, allowing centralized identity and access control.

8. AI-Driven Testing and Validation:

Run both Qlik and Power BI dashboards in parallel. By using Performance Analyzer, ensure DAX measures do not slow down the report. Validate calculations and KPIs. Use Computer Vision to compare the old Qlik dashboard and the new Power BI dashboard. Do performance testing and user acceptance testing to resolve any discrepancies that occur after deployment.

9. Deploy and Monitor with AI insights:

After validation, publish reports to the Power BI service. Continuously monitor usage and track refresh failures. It will help in maintaining reliability and user confidence.

Things to Be Considered Post Qlik to Power BI Migration

A Qlik to Power BI migration is considered successful only after careful planning and implementation of post-migration steps.

• Validate data accuracy: Data validation should be of top priority after moving from Qlik to Power BI. Compare both Qlik and Power reports side by side. Validate the calculations, measures, and KPIs. A small change in logic calculations between Qlik scripts and Power BI DAX can lead to mismatched results. 
• Monitor performance and usage: In Qlik, data is held in RAM, whereas in Power BI, performance depends on the storage mode. Verify that your Power Query steps are folding back to the source to prevent slow refreshes. Ensure that your new reports aren’t hitting memory ceilings.
• Training users: Whether it’s learning new visualization techniques or mastering data connections, upskilling your team for Power BI is essential for a successful migration from Qlik. While it may seem simple to adopt new tools, the reality is that focused training is vital for operational efficiency. When upskilling your team, you’ll need to make sure that they can be self-starters and work effectively with your data on your Power BI platform. To do this, some aspects you need to cover during training would include:
  
  • Foundational Training: Cover Power BI basics, including dashboards and data modeling.
  • Advanced Techniques: Teach DAX functions and custom visuals.
  • Data Security Practices: Emphasize access controls and compliance standards.
• Decommissioning Qlik: Once all data is validated, we can depend on the new Power BI platform alone. Running two BI platforms could become costly. Archive historical Qlik apps and confirm business sign-off from the stakeholders. 

How can Entrans help with Qlik to Power BI Migration?

Qlik to Power BI Migration involves data restructuring, logic rebuilding, performance tuning, governance planning, and user enablement. Parenting with a Migration expert like Entrans will bring in technical expertise and governance alignment. Entrans ensures smooth transition and long-term success with Power BI through a structured framework.

• We do a proper analysis of Qlik data files, load scripts, and extract business logic.
• We redesigned the data architecture to fit the Microsoft Fabric and Power BI Star Schema standards.
• Using AI-based digital engineering, we scan legacy Qlik codebases and uncover hidden business rules that need to be preserved.
• By utilizing Gen AI, we also assist in refactoring complex Qlik expressions into optimized DAX, reducing manual coding errors and accelerating the delivery timelines.
• We also offer pre-vetted migration experts who are specialized in the Microsoft data stack (Azure, Synapse, Fabric).
• We ensure that the new Power BI environment complies with enterprise standards.

Want to know more about it? Book a consultation call with us.

From Qlik to Power BI: An Insurance Renewal Success Story

For one of our clients, we have modernized the insurance renewal services from Qlik to Power BI. The client needed timely insights into policy renewals, expirations, and renewal initiation status to avoid revenue leakage. Challenges arose when complex dashboards were difficult to interpret, limited visibility into insurance agreement clauses, performance issues, and high maintenance effort. The client needed to migrate to the Power BI platform.

To solve this, we analyzed Qlik dashboards, KPIs, and calculations, recreated business logic using Power BI, Power Query, and DAX, and optimized data models. We migrated the details to Power BI, and through the Power BI dashboard, the customer was able to see KPI cards showing total policies, renewals, and expirations based on policy type, customer region, and renewal status.

Overall, we have shown more visibility to the customer about the insurance agreement, faster decision-making, and improved dashboard performance to improve customer retention.