QlikView & QlikSense: Build & Analyze Data Models Course

Editorial Take

This course bridges foundational Qlik skills with practical data modeling and security implementation, targeting learners aiming for roles in business intelligence and enterprise analytics. While not designed for absolute beginners, it offers structured progression through real-world workflows in QlikView and QlikSense.

Standout Strengths

• Hands-On Data Modeling: Learners engage directly with associative data models, mastering script-based data loading from diverse sources. This builds critical ETL skills essential for BI roles.
• QVD Optimization Focus: The course emphasizes efficient QVD usage, teaching how to reduce load times and improve performance—key for scalable enterprise deployments.
• Security Implementation: Role-based access and data-level security are integrated early, preparing users for compliance-sensitive environments like finance and healthcare.
• ERP Data Integration: Real-world ERP analysis scenarios provide context for applying Qlik tools in complex organizational systems, enhancing job readiness.
• Dynamic Visualization Training: Learners build interactive dashboards using QlikSense, gaining experience in user-driven analytics and visual storytelling techniques.
• Function Mastery: The course teaches advanced calculation functions, enabling precise KPI tracking and custom metric development across large datasets.

Honest Limitations

Limited Beginner Onboarding: The course assumes familiarity with data concepts and scripting, leaving new learners struggling without supplemental resources or foundational review sections.
• QlikSense Depth Gap: While QlikView is covered in depth, QlikSense content feels abbreviated, especially in cloud deployment and modern app development features.
• Lack of Peer Engagement: Minimal collaborative elements or discussion forums reduce opportunities for feedback and community-based learning.
• Assessment Light: Few graded assignments or capstone projects limit skill validation and portfolio-building potential for job seekers.

How to Get the Most Out of It

• Study cadence: Dedicate 4–5 hours weekly with consistent scheduling. Break modules into smaller sessions to absorb scripting syntax and data logic effectively.
• Parallel project: Apply lessons to a personal dataset (e.g., sales or inventory) to reinforce data modeling and dashboard design skills in real time.
• Note-taking: Document script patterns and function use cases. These notes become a reference library for future Qlik development tasks.
• Community: Join Qlik user groups and forums to ask questions and share dashboard examples, compensating for the course’s limited peer interaction.
• Practice: Rebuild visualizations multiple times with different data sets to internalize best practices in layout, interactivity, and performance tuning.
• Consistency: Complete exercises immediately after lectures while concepts are fresh, avoiding knowledge decay between sessions.

Supplementary Resources

• Book: 'QlikView Your Business' by Oleg Troyansky offers deeper insights into associative modeling and performance tuning beyond course scope.
• Tool: Use Qlik’s free trial environment to experiment with larger datasets and test security configurations hands-on.
• Follow-up: Enroll in Qlik’s official certification prep courses to validate skills and prepare for professional exams.
• Reference: Qlik Help Documentation provides up-to-date syntax guides and API references for ongoing learning.

Common Pitfalls

• Pitfall: Skipping data transformation steps can lead to model inefficiencies. Always validate scripts and optimize field naming early in the process.
• Pitfall: Overloading dashboards with visuals harms usability. Focus on clarity and purpose—each chart should answer a specific business question.
• Pitfall: Neglecting security layers risks data exposure. Always implement section access and user role testing before deployment.

Time & Money ROI

• Time: At 10 weeks, the course fits working professionals but requires discipline. Time investment pays off in practical BI skill acquisition.
• Cost-to-value: Priced moderately, it offers solid value for intermediate learners, though not the deepest resource available for Qlik mastery.
• Certificate: The credential supports resume building but lacks industry-wide recognition; practical skills matter more than the certificate itself.
• Alternative: Free Qlik tutorials exist, but this course structures learning and adds security and ERP context missing elsewhere.

Editorial Verdict

This course successfully equips intermediate learners with practical QlikView and QlikSense skills, particularly in data modeling, transformation, and security implementation. Its structured approach to loading data from multiple sources, optimizing QVD usage, and applying functions for advanced calculations makes it a valuable stepping stone for those entering business intelligence. The inclusion of ERP data analysis scenarios adds real-world relevance, especially for learners targeting enterprise environments. While the content is not cutting-edge, it remains technically accurate and pedagogically sound for its target audience.

However, the course has notable gaps—especially in QlikSense coverage and interactive learning components. The lack of robust assessments and peer engagement limits its effectiveness for self-learners seeking validation and community support. It also assumes prior data literacy, making it less accessible to true beginners. For the price, it delivers decent value, but learners should supplement it with hands-on practice and external resources. Overall, it’s a solid mid-tier option for those aiming to build foundational-to-intermediate Qlik skills with an emphasis on enterprise data workflows.