QlikView's associative data model is powerful but different from traditional SQL BI tools. Understanding its data model is the key to building dashboards that are fast, accurate, and not confusing to end users.

• Associative model: selecting a value in one chart automatically filters all other charts — this is the core user interaction pattern
• Data load script: transform data at load time, not at render time — pre-aggregated data loads significantly faster
• Set analysis: used for comparisons (current year vs prior year, selected region vs all regions) — master this before building complex dashboards
• Section access: row-level security built into the QVW file — restrict what data each user sees at login
• Performance: limit the number of charts on a single sheet; calculated dimensions are expensive — pre-calculate in the load script
• Naming conventions: use consistent field naming across all data sources loaded in a QVW — QlikView auto-joins on matching field names