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Qlik Sense Business Analyst Certification Exam - 2024 Sample Questions (Q21-Q26):

NEW QUESTION # 21
The sales manager is investigating the relationship between Sales and Margin to determine if this relationship is linear when choosing the dimension Customer or Product Category.
The sales manager wants to have the potential percentage Sales for each Stage (Initial to Won) of the sales process.
Which visualizations will meet these requirements?

  • A. Distribution plot: Alternative measures Sales and Margin, Alternatives dimensions Customer or Product category Bar chart: Dimension Stage, Measure Sales
  • B. Scatter plot: Measures X-axis Sales and Y-axis Margin, Alternative dimensions Customer or Product category Funnel chart: Segments Stage, Width Sales
  • C. Combo chart: Measures Sales and Margin, Dimensions Customer or Product category Pie chart: Dimension Stage, Measure Sales
  • D. Scatter plot: Measures X-axis Sales and Y-axis Margin, Dimensions Customer or Product category Bar chart: Dimension Stage, Measure Sales

Answer: B

Explanation:
For analyzing the relationship between Sales and Margin, a scatter plot is ideal, as it allows you to visualize the relationship between two measures (Sales and Margin) across various dimensions such as Customer or Product Category. The funnel chart is perfect for visualizing stages in a sales process, as it shows how sales progress from the initial stage to the final (Won) stage, with the width of each segment representing the total sales for each stage.
Key Concepts:
Scatter Plot: This type of chart is specifically designed to visualize the correlation or relationship between two measures, making it ideal for analyzing Sales versus Margin across different dimensions.
Funnel Chart: This chart is particularly suited for visualizing the sales stages, as it visually demonstrates the proportion of sales moving through each stage of the sales funnel.
Why the Other Options Are Less Suitable:
A . Scatter plot and Bar chart: While a scatter plot is correct for analyzing Sales and Margin, a bar chart won't adequately represent the different stages of the sales process as effectively as a funnel chart.
C . Combo chart and Pie chart: A combo chart could potentially work, but it would not show the relationship between Sales and Margin as clearly as a scatter plot. A pie chart is also less effective for representing stages in a sales funnel.
D . Distribution plot and Bar chart: A distribution plot does not effectively show the relationship between two measures, and a bar chart isn't the best choice for visualizing the stages of a sales process.
References for Qlik Sense Business Analyst:
Scatter Plot for Relationships: This chart type is highly recommended when exploring relationships between two continuous variables, such as Sales and Margin.
Funnel Charts: These are ideal for visualizing how data moves through various stages of a process, such as sales stages, from initial engagement to final sale.
Therefore, the combination of a scatter plot and a funnel chart provides the best solution, making B the correct answer.


NEW QUESTION # 22
A business analyst needs to create a visualization that compares two measures over time using a continuous scale that includes a range. The measures will be Profit and Revenue.
Which visualization should the business analyst use?

  • A. Scatter plot
  • B. Line chart
  • C. Bar chart
  • D. Bullet chart

Answer: B

Explanation:
A line chart is the most appropriate visualization for comparing two continuous measures (Profit and Revenue) over time. Line charts are designed to show trends and patterns over a continuous scale (such as time), making it ideal for this scenario where we need to observe how both Profit and Revenue vary across a period.
Key Concepts:
Continuous Scale: Line charts are specifically suited for continuous data like time, making them the preferred choice when tracking changes over time for multiple measures.
Dual Measure Comparison: A line chart allows you to plot two measures on the same axis, making it easy to compare their trends over the same period.
Why the Other Options Are Less Suitable:
B . Bullet chart: A bullet chart is used to compare a single measure against a target, not for tracking two measures over time.
C . Bar chart: Bar charts are better suited for comparing categorical data, not continuous measures over time.
D . Scatter plot: Scatter plots are used to compare relationships between two measures but are not suited for continuous time-based comparisons.
References for Qlik Sense Business Analyst:
Line Charts for Time Series Data: Line charts are the recommended visualization for comparing multiple measures over time in Qlik Sense, especially when working with continuous data like Profit and Revenue.
Thus, the line chart is the best choice for this scenario, making A the correct answer.


NEW QUESTION # 23
The business analyst creates one table by concatenating and joining several source tables. This has resulted in a table of several thousand rows that may have several columns containing between 30% and 70% null values. The business analyst needs to understand the level of null values in each field of this table to determine if this is an issue.
Which capability should the business analyst use?

  • A. Look at the tags fields for any indication that $null is associated to this field
  • B. Inspect each field in the Data model viewer and use the Subset ratio to determine the level of null values
  • C. Select each field in the Data model viewer and use the Density value to determine the level of nulls
  • D. Enable the Preview Panel in the Data model viewer and inspect the data table visually to determine the level of null values

Answer: C

Explanation:
The Density value in the Data Model Viewer provides a measure of how "dense" or "sparse" a field is in terms of data completeness. A higher density value means fewer nulls, while a lower value indicates more nulls. By checking the density value for each field, the business analyst can determine the percentage of non-null values, which is critical for understanding data quality and completeness.
Key Concepts:
Density Value: This is a measure in Qlik Sense that indicates the proportion of non-null values in a field. A field with a high density is mostly populated, while a lower density indicates a high proportion of null values.
Data Model Viewer: This tool allows analysts to inspect the structure and quality of data fields, including metrics such as density.
Why the Other Options Are Less Suitable:
B . Preview Panel: While the Preview Panel shows sample data, it does not provide a comprehensive measure of null values and is more suited for a quick glance rather than detailed analysis.
C . Tags fields with $null: This would show if the field contains any nulls, but it wouldn't quantify the level of nulls.
D . Subset Ratio: The subset ratio compares values across related tables, not null values within individual fields.
References for Qlik Sense Business Analyst:
Data Quality in Qlik Sense: Using the Density value is the best way to assess the proportion of null values in a field, making it ideal for the business analyst to understand the completeness of the data.
Thus, A is the correct answer because the density value provides the required insight into the level of nulls in each field.


NEW QUESTION # 24
The VP of Sales asks a business analyst to include a KPI object on the sales dashboard that shows total sales value for the year 2022, regardless of selections. Existing fields in the data model include Sales and Year.
How should the business analyst write the measure for the KPI object?

  • A. Sum( { < year="|" '2022,="" }="" /> } Sales)
  • B. Sum( { 1 < year="{" '2022'="" )="M /> ) Sales)
  • C. Sum( { $ < year="{" '2022*="" )="" /> } Sales)
  • D. Sum( 1 { < year="(" '2022'="" )="" /> ) Sales)

Answer: B

Explanation:
In this scenario, the VP of Sales wants to see the total sales for the year 2022 regardless of selections. This requirement is best handled using Set Analysis in Qlik Sense. The key to achieving this is using the set identifier 1, which ignores the user's selections and ensures the calculation is based on the entire dataset. The expression Sum( { 1 < year = { '2022' } > } Sales) calculates the sum of sales for the year 2022, irrespective of any other selections made in the app.
Key Concepts:
Set Identifier 1: This identifier ensures that the calculation is performed on the entire dataset, ignoring any selections or filters applied by the user.
Year Filtering: The expression < year = { '2022' } > ensures that only sales from the year 2022 are included in the calculation.
Why the Other Options Are Less Suitable:
A . Sum( { < year = '2022' > } Sales): This is incorrectly formatted, and the pipe (|) symbol should not be used in this context.
B . Sum( { $ < year = { '2022' } > } Sales): The $ set identifier respects the current selections, which is not what is needed in this case, as the VP wants the value to be shown regardless of selections.
D . Sum( 1 { < year = { '2022' } > } Sales): The placement of 1 is incorrect in this expression.
References for Qlik Sense Business Analyst:
Set Analysis: Qlik Sense's Set Analysis allows analysts to control what data is used in a calculation, regardless of user selections. The set identifier 1 ensures that selections are ignored, which is essential for showing fixed data such as total sales for a specific year.
Thus, the correct expression to show the total sales for 2022, regardless of user selections, is C.


NEW QUESTION # 25
A business analyst is working with a customer to refine the end user experience. The customer has the following requirements:
* Ability to provide these charts to a specific user group
* Minimize the number of navigation clicks between charts
* Achieve fastest screen response time when switching between charts
* Maximize the chart size in terms of screen real estate
Which action should the business analyst take to meet the requirements?

  • A. Create several sheets (one sheet per client) and use buttons to navigate between sheets
  • B. Create a single sheet with every required chart on this single sheet
  • C. Use Conditional show on all charts and overlay the charts in the same location
  • D. Use a container object to host the required visualizations

Answer: D

Explanation:
The best solution for minimizing navigation clicks, maximizing screen real estate, and ensuring fast response times is to use a container object. A container object allows the business analyst to house multiple charts within a single visualization, making it easy for users to switch between them with minimal navigation. This also ensures that only one chart is rendered at a time, which improves screen response time.
Key Concepts:
Container Object: This feature allows multiple charts to be placed in one object, minimizing navigation clicks and maximizing screen real estate, as users can switch between charts within the same view.
Fast Response Time: Since only one chart is visible at a time, rendering performance is optimized, ensuring fast responses when switching between visualizations.
Why the Other Options Are Less Suitable:
A . Conditional show: This could lead to performance issues, as multiple charts would be rendered simultaneously, slowing down response time.
B . Single sheet with all charts: This would clutter the screen and reduce chart size, making it less optimal for user experience.
D . Several sheets with buttons for navigation: This increases the number of navigation clicks, which contradicts the requirement of minimizing navigation.
References for Qlik Sense Business Analyst:
Container Object for Multiple Visualizations: Qlik Sense recommends container objects when you need to show multiple charts with minimal navigation and maximum screen real estate.
Thus, using a container object to host the required visualizations is the best solution, making C the verified answer.


NEW QUESTION # 26
......

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