Qlik QSBA2024 Exam Dumps

A combo chart is the most suitable visualization to show the value of sales for each month along with a rolling 3-month summary. The combo chart allows you to combine different types of visualizations, such as bars for monthly sales values and a line for the rolling 3-month summary. This provides a clear comparison and tracking of sales trends over time.

Key Concepts:

Rolling Summary: In this case, a 3-month rolling summary can be shown as a line measure in the combo chart, while the sales values for each month can be shown as bars.

Combo Chart: This visualization is ideal for comparing multiple measures on the same axis, such as individual sales values and aggregated rolling summaries.

Why the Other Options Are Less Suitable:

A . Scatter plot: A scatter plot is used to display the relationship between two variables, not to show time-based trends or rolling summaries.

B . Mekko chart: Mekko charts are used for categorical data and comparisons across categories, not for time-based analysis.

D . Pie chart: Pie charts are best suited for showing parts of a whole and are not appropriate for visualizing time-based data or rolling summaries.

References for Qlik Sense Business Analyst:

Combo Charts for Time Series Data: Combo charts are highly recommended when there is a need to compare different types of measures (like individual sales vs. rolling averages) over time in Qlik Sense.

Thus, a combo chart provides the most effective solution for showing both monthly sales values and the rolling 3-month summary, making C the correct answer.

The Multi KPI object is designed to display multiple key measures in a compact and visually appealing format, making it ideal for a dashboard that requires a minimal number of visualizations but must present multiple key metrics. By using master visualizations, the business analyst ensures consistency and reusability across different sheets. This setup also allows for easy navigation through the app, as users can drill down into more detailed sheets when needed.

Key Concepts:

Multi KPI: This visualization allows multiple key performance indicators (KPIs) to be displayed in a single object, reducing the need for multiple charts or visualizations while ensuring that critical metrics are visible.

Master Visualizations: These ensure that KPIs are consistent across the app and can be reused as needed, helping to maintain a clean and efficient dashboard.

Why the Other Options Are Less Suitable:

B . Dynamic text and image linked objects: This could work for navigation, but it wouldn't meet the requirement of displaying multiple key measures in a minimal number of visualizations.

C . Bookmark: A bookmark is used to save a particular state of selections but isn't useful for showing multiple KPIs simultaneously.

D . Container: While containers can hold multiple visualizations, the Multi KPI object is more suited to displaying multiple key measures in a compact space.

References for Qlik Sense Business Analyst:

Multi KPI for Compact Dashboards: Qlik Sense recommends using Multi KPI objects when there is a need to display multiple key metrics in a minimalistic format.

Thus, A is the best choice to meet the CEO's requirements, making it the correct answer.

A scatter plot is the most appropriate visualization for analyzing the correlation between Product Sales ($), Order Volume, and Margin %. Scatter plots are ideal for showing relationships between two or more continuous variables, which is crucial for identifying trends or correlations among these measures.

Key Concepts:

Scatter Plot: This chart type is specifically designed to display correlations between measures, making it the ideal choice for visualizing relationships between Product Sales, Order Volume, and Margin %.

Multiple Measures: Scatter plots in Qlik Sense can plot two measures on the X and Y axes and can use colors or bubbles to represent additional measures (such as Margin %).

Why the Other Options Are Less Suitable:

A . Multi KPI: A Multi KPI displays multiple metrics but doesn't show correlations between them.

B . Combo chart: A combo chart combines bar and line charts but is not suited for analyzing correlations between multiple continuous measures.

D . Pivot table: While useful for data aggregation, a pivot table does not provide a clear visualization of correlations between measures.

References for Qlik Sense Business Analyst:

Scatter Plot for Correlation Analysis: Scatter plots are recommended in Qlik Sense when exploring relationships between multiple continuous variables.

Thus, the scatter plot is the most effective visualization for analyzing the correlation between Product Sales, Order Volume, and Margin %, making C the correct answer.

To meet the needs of both the internal analyst team and the sales team, the best solution is to create two separate apps: one designed specifically for mobile use and another for internal use. Mobile devices require different UI considerations, such as simpler, touch-optimized layouts, while the internal team can benefit from a more detailed app optimized for desktop use. Designing separate apps ensures that both teams have a tailored experience that suits their specific devices and use cases.

Key Concepts:

Mobile Optimization: Mobile devices require apps that are streamlined and optimized for smaller screens, while internal users on desktop computers can handle more complex layouts and detailed reports.

Separate Apps: Creating separate apps ensures that each team gets the best user experience tailored to their needs.

Why the Other Options Are Less Suitable:

A . One app with a specific extension for mobile users: While extensions can provide some mobile functionality, they don't offer the flexibility and optimization needed for a fully mobile-friendly experience.

C . A mashup with various objects: A mashup may provide flexibility, but it could be overly complex for this requirement and wouldn't necessarily offer an optimal mobile experience.

D . One app with various objects: This could complicate the user experience for both teams, as mobile users may struggle with objects that are not optimized for their devices.

References for Qlik Sense Business Analyst:

Mobile vs. Desktop App Design: Qlik Sense recommends optimizing apps for specific devices to ensure the best user experience for both desktop and mobile users.

Thus, B is the correct answer because it provides the best solution for both the mobile sales team and the internal analyst team, making it the verified answer.

A scatter plot is the best choice for visualizing outliers, clustering, and products that are above the median sales volume. Scatter plots are excellent for showing relationships between two variables (like sales volume and margin %) while providing the ability to highlight outliers. By using K-Means clustering to color the products, the business analyst can visually group similar products. Additionally, adding a median sales volume reference line makes it easy to identify which products are above or below the median.

Key Concepts:

Scatter Plot: This visualization is ideal for detecting outliers and understanding the distribution and clustering of data points.

K-Means Clustering: This technique groups similar data points (products) based on their values, which helps to identify patterns visually.

Median Reference Line: Adding a reference line for median sales volume ensures that the analyst can easily see which products are performing above or below the median.

Why the Other Options Are Less Suitable:

A . Pivot table: While a pivot table could show aggregated data, it is not as effective for visualizing outliers or clustering as a scatter plot.

B . Treemap: A treemap can show hierarchical relationships but is not as effective for identifying clusters or outliers.

C . Combo chart: A combo chart is not as well-suited for visualizing clustering and outliers as a scatter plot.

References for Qlik Sense Business Analyst:

Outliers and Clustering Visualization: Qlik Sense recommends scatter plots for visualizing relationships between two measures and for detecting outliers and clustering in the data.

Thus, creating a scatter plot with K-Means clustering and a median sales volume reference line is the best approach, making D the verified answer.