A combo chart is specifically designed to display two different measures (like actual sales and a percentage) using different visual encodings (bars and a line) on a shared axis. This allows for an immediate, intuitive comparison of the absolute value and the relative performance metric in one view, meeting the requirement for a single, clear visual.

The Qlik load script executes sequentially. If a WHERE clause tries to filter on a field that is defined in a subsequent LOAD statement (or later in the same statement), the field does not yet exist in the table’s data model context, resulting in a ‘Field not found’ error. The script logic must ensure fields are loaded before they are referenced in conditions.

The {$} set modifier explicitly references the current selection state. If the expression is producing unexpected results, it is not because {$} is behaving incorrectly by default; it is working as designed. The issue likely lies in the logic of the expression itself (e.g., incorrect set operators or modifiers within the expression) or a misunderstanding of how the current selections affect the underlying data.

The If() function is the primary conditional function used in Qlik to create custom groupings or classifications based on specified conditions. A statement like `If(Sum(Sales) > 10000, ‘High’, If(Sum(Sales) > 5000, ‘Medium’, ‘Low’))` would create the required tiered dimension. The Class() function creates numeric intervals, not textual groups.

The optimal approach is to create a synthetic or composite key that uniquely identifies the combination of Month and ProductID in both tables. By naming this key field identically (e.g., ‘BudgetKey’) in both LOAD statements, Qlik’s associative engine will automatically link the Sales and Budget records for the same Month and ProductID, enabling seamless comparison without duplicating data or losing granularity.

The Sort tab in the chart properties provides direct control over how dimension values are ordered in that specific object. Selecting ‘Sort by Expression’ and choosing ‘Y-value’ (which corresponds to the chart’s primary measure) will sort the regions based on the calculated bar length (sales amount) in descending order, achieving the desired automatic sorting.

The set identifier `{1}` represents the full set of all possible records in the application’s data model, disregarding any and all user selections. In this expression, the numerator calculates sales for 2023 within the current selections, while the denominator calculates total sales across all data unconditionally, giving the share of 2023 sales relative to the grand total.

Mobile screens have limited space and are primarily interacted with via touch. The best practice is to design for a vertical flow, placing key visualizations in a single column. This makes them easy to view and interact with by tapping and scrolling. Charts should be simplified and focused on the most critical KPIs to avoid clutter and poor usability.

The `Sum(TOTAL Sales)` expression calculates the sum of Sales across all rows in the current chart context while ignoring the dimensional breakdown. In a table with Salesperson as the dimension, `Sum(TOTAL Sales)` gives the total for all salespeople shown (which is filtered by the user’s region selection). Dividing each row’s sales by this total yields the correct within-context percentage.

A combo chart is specifically designed to display two different measures (like actual sales and a percentage) using different visual encodings (bars and a line) on a shared axis. This allows for an immediate, intuitive comparison of the absolute value and the relative performance metric in one view, meeting the requirement for a single, clear visual.0