QSBA2024 Exam Dumps - Qlik Sense Business Analyst Certification Exam-2024

In Qlik Sense, the'By Dimension'and'Persistent colors'options in the Colors property panel ensure that the same dimension values have the same color across multiple charts. This is especially useful when you have two or more side-by-side charts sharing a common dimension, like customer names in this case. Persistent colors guarantee consistency in color assignment, helping users visually track the same dimension across different visualizations.

Key Concepts:

By Dimension: This option ensures that each unique value of a dimension (e.g., customer name) gets a distinct color across all charts that use this setting.

Persistent Colors: This feature ensures that the colors remain the same between charts, making the visual comparison across charts easier for the users.

Why the Other Options Are Less Suitable:

A. Use nested IF statements to set the colors by expression for each dimension value: While this would work, it would be unnecessarily complex to maintain and manage, especially with many dimension values.

B. Define the color values in the master measures and use the color library: This would only apply if the goal was to set colors based on measures, not dimensions. In this case, dimension consistency is required, not measure-based coloring.

D. Use the FieldIndex function to set the colors by expression for each dimension value: This would involve writing complex expressions that would not be as straightforward as using the built-in functionality of 'By Dimension' and 'Persistent colors'.

References for Qlik Sense Business Analyst:

Color Consistency Across Charts: The 'By Dimension' and 'Persistent colors' settings are recommended in Qlik Sense documentation when creating multi-chart layouts with shared dimensions, ensuring visual coherence across different charts.

ThePersistent colorsandBy Dimensionsettings offer a straightforward and maintainable way to create color associations across charts, making optionCthe verified solution.

In this Section Access script, the roles and access to data for different users are defined based on theSACOUNTRYfield. Here’s how the data access will work:

ADMIN: The ADMIN user has access to all data because the * in theSACOUNTRYfield allows full access to all countries in the dataset.

USER1: This user has access toSpainandFrancebecause theSACOUNTRYfield specifies these countries for USER1.

USER2: This user has access toUnited Kingdombecause theSACOUNTRYfield specifies only the UK for USER2.

Key Concepts:

Section Access: This feature in Qlik Sense controls which data users can see based on their login credentials. The access rights are controlled through fields likeACCESS,USERID, andSACOUNTRYin this case.

Why the Other Options Are Less Suitable:

B and C: These suggest that users won’t see data they have access to, which contradicts the definedSection Accessscript.

D: This incorrectly assumes that ADMIN cannot see Germany, which is not defined in the script.

References for Qlik Sense Business Analyst:

Section Access Best Practices: In Qlik Sense, Section Access tables define the data that users can see, and the use of * for the ADMIN role ensures access to all data.

Thus,Ais the correct answer because it matches the expected data access behavior based on the script, making it the verified answer.

When users need control over how many product categories are shown in a bar chart, the most effective solution is to use avariable input object. This allows users to dynamically adjust the number of categories displayed.

A. Create a variable and variable input object and use the variable in the dimension limit field.This is the correct solution. By creating avariableand using theVariable Input object, the usercan dynamically control the number of product categories shown in the bar chart by adjusting the dimension limit. This method provides flexibility and an intuitive interface for the user.

B. Use firstsortedvalue() function to extract the required product categories.The firstsortedvalue() function is typically used to extract the first occurrence of a value based on sorting criteria, but it’s not the best approach for controlling the number of displayed categories dynamically.

C. Create a variable and variable input object and use the variable in the sales expression.While variables can be used in expressions, this approach is less efficient than using the dimension limit field, which is specifically designed for controlling the number of displayed values.

D. Use a rankQ function in the sales expression.The rankQ function ranks data, but it’s not the most efficient or intuitive method for dynamically controlling the number of product categories displayed in a bar chart. It would require more complex expressions compared to the straightforward use of a variable in the dimension limit field.

Key Qlik Sense Business Analyst References:

TheVariable Input objectallows users to interact with and adjust variables within the app. This is ideal for giving users control over visual elements like the number of categories displayed in a chart.

TheDimension Limit fieldis specifically designed to control how many items (like product categories) are shown in a chart based on a ranking or expression.

Thus, the best approach to allow users to control the number of product categories displayed is tocreate a variable and variable input object, and use the variable in the dimension limit field.

When working with Qlik Sense apps, a business analyst often encounters situations where visualizations may be highly similar between different apps, even if the underlying data models differ. In such cases, efficiency is crucial, and Qlik Sense provides several methods to reuse visualizations across apps. Let's break down the options:

A. Add the base visualization to the master items and use it as a template for the new visualization.This option suggests adding the base visualization to the master items. While master items are useful for reusing dimensions, measures, and visualizationswithin the same app, they do not easily transfer across apps. In this case, since the visualization is required in a different app, this approach would not be the most efficient or feasible.

B. Note the properties of the base visualization and create the new visualization from scratch.This option involves manually noting the properties and then replicating them in the new app. While this would work, it is labor-intensive and increases the likelihood of human error, especially in complex visualizations. It is not an efficient solution for business analysts looking to save time.

C. Copy and paste the visualization between the apps, and update the data properties in the new app.This is the most efficient solution. Qlik Sense allows for thecopying and pasting of visualizations between different apps, and you can then adjust the properties to fit the new data model. This option enables the business analyst to leverage existing visual work without having to recreate it from scratch. Updating the data properties, such as dimensions and measures, ensures that the visualization functions correctly with the new data model.

D. Open both apps at the same time. Drag the base visualization between apps, then update the data properties.While this seems like a practical option, Qlik Sense does not allow users to drag and drop visualizations directly between different apps. As a result, this method is not possible.

Key Qlik Sense Business Analyst References:

Copying and pasting visualizationsis a common practice in Qlik Sense when working between different apps. The ability to quickly replicate and adapt visualizations across apps helps streamline the development process.

Adjustingdata propertiessuch as dimensions and measures ensures that visualizations adapt to different data models without the need for full recreation.

Efficiency and error reduction are critical in app development, andcopy-paste functionalitiesare specifically designed to reduce manual work in such scenarios.

In conclusion, the correct and most efficient action for the business analyst to take isC, copy and paste the visualization, and then update the relevant data properties.

In Qlik Sense,default bookmarksallow a set of selections to be applied automatically whenever the app is opened. By creating a bookmark and setting it as the default, the business analyst ensures that the required selections are applied every time the app is opened, which meets the requirement of consistently applying the same selections for all users.

Key Concepts:

Default Bookmark: A default bookmark automatically applies the saved selections when an app is opened, ensuring consistency without manual input from users.

Bookmarking: This feature allows users to save specific selections or states of a dashboard for later use.

Why the Other Options Are Less Suitable:

A. Section Access: Section Access controls data access and security, not default selections.

B. Mashup with API: While this could technically work, it's unnecessarily complex and requires custom coding.

C. Sheet Action: A sheet action could apply a bookmark but would not ensure that the selections are applied at the time of app opening.

References for Qlik Sense Business Analyst:

Default Bookmark for Predefined Selections: This feature is commonly used to ensure that specific selections are always applied when an app is opened.

Thus,Dis the best solution for applying default selections, making it the correct answer.

Aline chartis 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, theline chartis the best choice for this scenario, makingAthe correct answer.

The business analyst needs to optimize the app for performance and ensure that users only see data from the past two years, without cardholder information, and that the data is updated daily. Bydeselecting the Cardholder and time fieldsin the Data Manager, the analyst ensures that sensitive information is not loaded. Applying afilter to extract data based on transaction yearensures that only relevant data (the last two years) is included in the app, improving performance. Lastly, requesting a daily reload task from the system administrator ensures that the app stays up to date.

Key Concepts:

Deselecting Fields: This removes unnecessary fields, such as Cardholder information, from the data model, which improves performance and ensures privacy.

Filtering Data: Applying a filter to limit data to the last two years reduces the dataset size and improves app responsiveness.

Daily Reload Task: Requesting a daily reload ensures that the app’s data stays current, meeting the requirement for daily updates.

Why the Other Options Are Less Suitable:

A. Delete Cardholder and time fields, use bookmark: A bookmark is not an efficient solution for filtering by transaction year.

B. Set analysis and API reload: Set analysis works within the app but does not optimize the data load itself. Using an API for reload tasks is unnecessarily complex.

C. Use filter pane and auto-calendar: While auto-calendar fields can be useful, they don’t optimize the data loading process for performance.

References for Qlik Sense Business Analyst:

Efficient Data Loading: Qlik Sense recommends filtering data at the load stage to improve performance, especially when dealing with large datasets.

Thus,Dis the correct solution, making it the verified answer.