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Qlik Sense Business Analyst Certification Exam - 2024 Sample Questions (Q43-Q48):

NEW QUESTION # 43
A customer is developing over 100 apps, each with several sheets that contain multiple visualizations and text objects. The customer wants to standardize all colors used every object across every app. The customer also needs to be able to change these colors quickly, as required.
Which steps should the business analyst take to make sure the color palette is easily maintained in every app?

A. * Store color definitions within a .qvd file
* Have each app load this file as a data island in the model
* Have every object select its required color property from the rows within the data island
B. * Create all color expressions as variables in a text file
* Load it in each app with an include statement
* Use these variables in the color property of all objects
C. * Develop the first app with every variation of object and visualization that will be required
* Duplicate this app to create every other app
* Remove the variations that are not required and adjust the ones needed
D. * Design all base objects as master visualizations
* Link each object in each app to the relevant master visualization
* Adjust the data properties as required

Answer: B

Explanation:
In scenarios where a customer needs to standardize colors across multiple apps and be able to update them quickly, using variables in combination with an include statement is the most flexible and maintainable approach.
A . Design all base objects as master visualizations and link each object in each app to the relevant master visualization.
While master visualizations help with consistency within a single app, they don't offer an easy way to update all apps globally. You would need to manually update the colors in every master visualization in each app, which is not efficient for large-scale management.
B . Develop the first app with every variation of object and visualization and duplicate this app.
Duplicating apps will create maintenance challenges. Each app would need to be updated individually if colors or other settings change, which is not scalable for over 100 apps.
C . Create all color expressions as variables in a text file, load it in each app with an include statement, and use these variables in the color property of all objects.
This is the most efficient solution. By storing color definitions in a text file and loading them with an include statement, the business analyst can update the colors in one place, and these updates will be reflected across all apps that use the file. This method ensures easy maintenance and flexibility.
D . Store color definitions within a .qvd file and load it as a data island.
While using a .qvd file is possible, it's not as straightforward as using variables and an include statement. Data islands are typically used for selection purposes, and this method would introduce unnecessary complexity in managing colors.
Key Qlik Sense Business Analyst References:
Variables are widely used in Qlik Sense for managing repeated expressions or values like colors. They can be defined once and reused throughout the app.
Include statements allow external files (like text files containing variables) to be loaded into apps, ensuring that updates made to the text file are automatically reflected in all apps that use it. This creates a flexible and scalable solution for managing standardization across multiple apps.
Thus, the best way to maintain a standardized color palette across all apps is to create all color expressions as variables in a text file and load them into each app using an include statement.

NEW QUESTION # 44
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. Select each field in the Data model viewer and use the Density value to determine the level of nulls
B. Inspect each field in the Data model viewer and use the Subset ratio to determine the level of null values
C. Enable the Preview Panel in the Data model viewer and inspect the data table visually to determine the level of null values
D. Look at the tags fields for any indication that $null is associated to this field

Answer: A

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 # 45
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( { < year="|" '2022,="" }="" /> } Sales)
C. Sum( { 1 < year="{" '2022'="" )="M /> ) Sales)
D. Sum( 1 { < year="(" '2022'="" )="" /> ) Sales)

Answer: C

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 # 46
A business analyst receives an image of a dashboard from the HR Director and is asked to recreate the image in Qlik Sense. The image shows charts for:
* Company employee structure
* Average employee salary by region
* Geographical representation of office capacity
* Company retention over time
Which charts will meet these analysis requirements?

A. Map chart, org chart, line chart, bar chart
B. Line chart, network chart, bar chart, map chart
C. Map chart, grid chart, line chart, KPI chart
D. Line chart, sankey chart, map chart, bar chart

Answer: A

Explanation:
To recreate the dashboard image provided by the HR Director, the following charts are needed:
Map chart: To show the geographical representation of office capacity.
Org chart: To show the company employee structure.
Line chart: To show company retention over time.
Bar chart: To show average employee salary by region.
Key Concepts:
Map Chart: Used to visualize geographical data, such as office capacity across different locations.
Org Chart: Ideal for displaying hierarchical structures, such as the employee structure of a company.
Line Chart: Best suited for showing trends over time, such as employee retention.
Bar Chart: A good choice for comparing salaries across regions.
Why the Other Options Are Less Suitable:
A . Sankey chart: This chart is used for flow or process analysis, not employee structure.
B . Network chart: Network charts show relationships but are not ideal for hierarchical structures like an org chart.
C . Grid chart and KPI chart: These charts are not well-suited for the types of data required in this scenario.
References for Qlik Sense Business Analyst:
Chart Selection for HR Dashboards: Qlik Sense provides various visualization options, and selecting the correct chart for each type of data is essential for accurate and clear representation.
Thus, the correct combination of charts is D-Map chart, org chart, line chart, and bar chart-making it the verified answer.

NEW QUESTION # 47
A business analyst needs to build a chart that enables users to analyze the correlation between the following measures for all products:
* Product Sales ($)
* Order Volume
* Margin%
Which visualization should the business analyst use?

A. Combo chart
B. Pivot table
C. Scatter plot
D. Multi KPI

Answer: C

Explanation:
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.

NEW QUESTION # 48
......

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