Category: Learning Paths & Courses
October 8, 2025
Qlik Set Analysis vs IF(): Which Is Actually Faster?
Set Analysis is a powerful syntax in Qlik that lets you apply calculations to specific subsets of your data — often 3-8x faster than a traditional IF() function. This guide covers Set Analysis fundamentals, Dollar-Sign Expansion, Set Operators, AGGR(), and the flag method for ultimate performance.
October 7, 2025
Qlik Sense Data Modeling Course: The Complete Guide (28 Articles)
28 articles that take you from beginner to Qlik Sense Data Architect. Learn to load data, build optimal data models, tune performance, and implement enterprise architectures. What is the Qlik Sense Data Modeling Course? This course covers all key aspects of Qlik Sense data modeling – from your first LOAD statement to complex enterprise architectures with the Three-Stage Pattern, performance tuning…
October 7, 2025
Qlik Sense IterNo() & AUTOGENERATE: Loops, Sequences & Record Expansion
Qlik Sense Course – Article 16 of 28. What is IterNo()? A counter function that returns the current iteration number (1, 2, 3…) in WHILE loops – perfect for date ranges, sequences, and record expansion! Learn how to use the power trio of IterNo() + AUTOGENERATE + WHILE for generating sequences and expanding records.
October 6, 2025
Qlik Master Calendar: Build Date Dimensions That Work
📚 Qlik Sense Course – Article 15 of 28 ← Previous Article: Time-Based Data – IntervalMatch & Calendar → Next Article: IterNo() & AUTOGENERATE Patterns What is a Master Calendar? A Master Calendar is a complete, gap-free table of all date values with pre-calculated time dimensions (Year, Quarter, Month etc.) – for performance and consistent time analysis. What you…
October 6, 2025
Temporal Data in Qlik Sense: IntervalMatch & Master Calendar Complete Guide
Qlik Sense Course – Article 14 of 28. What is IntervalMatch? A special Qlik function that automatically maps individual points in time (e.g., sale date) to time periods (e.g., budget periods) – without complex JOINs. Learn IntervalMatch, Master Calendar generation, Date Island patterns, and fiscal year handling.
October 6, 2025
Slowly Changing Dimensions Type 2 in Qlik Sense: Complete Implementation Guide
Qlik Sense Course – Article 13 of 28. What is SCD Type 2? A method for historizing dimension changes. When a customer switches regions, the old version is kept and a new one is created – keeping historical analyses accurate. Learn how to implement SCD2 with hash-based change detection, surrogate keys, and point-in-time lookups.
October 6, 2025
Link Tables for Many-to-Many Relationships in Qlik Sense: The Complete Guide
Qlik Sense Course – Article 12 of 28. What is a Link Table? A Link Table (also called Bridge Table) resolves many-to-many relationships: one customer buys multiple products, one product is bought by multiple customers. The Link Table connects both sides cleanly – without Synthetic Keys! Learn how to build composite keys and optimize performance.
October 6, 2025
Fact vs Dimension in Qlik Sense: Making the Right Design Decisions
Qlik Sense Course – Article 11 of 28. What is the difference between Fact and Dimension? Facts contain transactional, measurable data (revenue, quantities) – they answer ‘What happened?’. Dimensions contain descriptive data (customer, product) – they answer ‘Who/What/Where/When?’. Learn how to classify tables correctly and design performance-optimal data models.
October 5, 2025
Star Schema in Qlik Sense: The Complete Guide to Performance & Clarity
Qlik Sense Course – Article 10 of 28. Learn how to implement star schema architecture in Qlik for 3-8x better expression performance, reduce memory consumption by 40-60%, and model clean business hierarchies without circular references or synthetic keys. Covers Simple Star, Multiple Facts, and Conformed Dimensions patterns.
October 5, 2025
Qlik Sense Synthetic Keys & Circular References: How to Identify and Fix Data Model Problems
Learn how to identify and resolve synthetic keys and circular references in Qlik Sense data models. This guide covers field renaming strategies, architectural decoupling, preventive naming conventions, and troubleshooting common data modeling problems.