QSBA2024 Sample Questions & Answers

False. While the Data Manager's recommendations are a powerful guide, a business analyst must always use their domain knowledge to validate them. An association might be technically correct based on field names and data profiling, but contextually wrong for the business logic. For example, associating OrderDate with ShipDate could be recommended but would create a flawed model. Analysts must review and confirm that the recommended associations make logical sense for the analysis.

The total qualifier is the key. Sum(Sales) calculates the sales for the current dimension (Salesperson). Avg(total Sales) calculates the average of sales for all salespeople within the same region, ignoring the Salesperson dimension but respecting the Region dimension. This provides the correct regional average for the comparison.

The 'Dashboard' layer in the DAR methodology is intended for at-a-glance monitoring. It should consist of high-level, summary visualizations like KPIs, gauges, and simple charts that quickly convey status and performance without requiring deep interaction or reading.

This is the correct approach. Snapshots are used to capture a visualization in a specific state (e.g., with certain selections applied) and embed it as a static image in a story. For interactivity, embedding a live sheet allows the presenter to make selections and interact with the objects directly during the presentation. This combination meets all requirements.

The Data load editor is the correct place to perform data cleansing and transformation. By using an expression like Text(PostalCode) as PostalCode in the LOAD script, the analyst ensures that all values in the field are loaded as a consistent text data type before they are stored in the data model. This solves the problem at the source for the entire application.

White represents the 'possible' values. These are data values that are associated with the current selections (green) and are therefore still available for further filtering. This is a core concept of the associative experience, showing the user what is still relevant based on their choices.

This expression uses set analysis to correctly calculate YoY growth. Sum({ } Sales) calculates sales for the currently selected max year. Sum({ } Sales) calculates sales for the prior year by modifying the Year selection within the expression. The formula (Current - Previous) / Previous then gives the correct growth percentage, independent of the chart type.

Section Access performs data reduction at the time of app open. The data for countries the user is not authorized to see is completely removed from the data model for their session. Therefore, the user's app will behave as if 'USA' is the only country that exists in the data set.

Master Items (specifically Master Measures) are the designated feature for creating a centralized, reusable library of calculations. They can be given user-friendly names, descriptions, and tags. If the logic needs to be updated, it only needs to be changed in one place (the Master Measure), and all linked visualizations will update automatically. This is the core of governed self-service.

The dimension determines what each individual bubble represents. In this case, each bubble is a unique production run.

A scatter plot requires two measures to define the position of each bubble on the X and Y axes. These correspond to Volume and Defect Rate.

To make the scatter plot a bubble chart, a third measure is used to control the size of the bubbles. This is configured in the specific 'Bubble size' property.