QSBA2024 Qlik Sense Business Analyst Certification Exam-2024 Questions and Answers

To dynamically highlight a specific product bar in a bar chart based on conditions, the best approach is to use theColor By Expressionfeature under the Appearance settings in Qlik Sense. This feature allows you to apply conditional formatting to bars, changing their color dynamically based on expression logic.

A. A Color By Expression property under AppearanceThis is the correct answer. TheColor By Expressionproperty allows the business analyst to dynamically color bars in the chart based on specific conditions. The expression can be set to highlight a specific product bar only when certain conditions are met, and the color can be customized to make it stand out.

B. A Dimension reference line add-onDimension reference lines are used to show thresholds or important values along the axes, but they do not dynamically color the bars or add conditional labels to them. This would not achieve the desired effect.

C. An Alternative dimension with a calculationAlternative dimensions allow users to switch between different dimensions in the same chart, but they do not provide dynamic highlighting or conditional visibility for labels.

D. A reference line add-on under PropertiesReference lines are used to mark specific values or thresholds in a chart, but they do not interact with the dynamic coloring or visibility of labels on individual bars.

Key Qlik Sense Business Analyst References:

Color By Expressionis a powerful feature in Qlik Sense that allows dynamic customization of chart colors based on expressions, making it ideal for highlighting specific data points or conditions.

This feature provides great flexibility in creating visually engaging and interactive charts that respond to changes in the underlying data or user selections.

Thus, the correct way to highlight a specific product bar with a dynamic label is to useColor By Expression under Appearance.

For the KPI object that meets the requirements of comparingCurrent Year (CY)sales againstLast Year (LY)sales, while ensuring the KPI remains static regardless of selections, we need to leverageSet Analysiswith the 1 identifier. This ensures the KPI ignores any selections made by the user.

OptionAuses the correct structure of Set Analysis that compares CY sales to LY sales within theAPACregion, and the 1 set identifier ensures the KPI does not change based on selections. The logic is structured as follows:

Sum({1 <region={"apac"}, year={$(=max(year))}>} Sales)computes the sales for the APAC region for the current year (CY).

Sum({1 <region={"apac"}, year={$(=max(year)-1)}>} Sales)computes the sales for the APAC region for the previous year (LY).

This expression will ensure that the comparison of sales between CY and LY is made, without being affected by user selections.

Key Concepts:

Set Analysis with 1: The 1 set identifier ensures that selections made by users do not affect the result, making the KPI static.

Comparison of CY vs. LY: The use of $(=max(year)) and $(=max(year)-1) ensures that the current and previous years are dynamically compared.

Why the Other Options Are Less Suitable:

B, C, and D: While these options use a similar structure, they do not correctly handle the measure structure or have syntactical issues. Only OptionAproperly utilizes the 1 set identifier and dynamic year comparison for the APAC region.

References for Qlik Sense Business Analyst:

Set Analysis for Static KPIs: Using the 1 set identifier in Qlik Sense ensures that a KPI remains static and unaffected by user selections, which is essential for business requirements like this.

Thus,Ais the correct choice because it correctly computes the required static KPI for the APAC region, making it the verified answer.

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.

The best approach to allow users to frequently adjust the profit threshold in the visualization is to use avariablecontrolled by avariable slider. This method allows each user to adjust the threshold value independently without requiring any changes to the data model or the visualization itself. Given that the user base consists of heavy Excel users, using a slider provides a familiar and intuitive way to interact with the threshold.

Key Concepts:

Variables and Sliders: Variables can be used to store threshold values, and sliders provide an easy way for users to adjust those variables interactively.

User Interaction: A variable slider is a user-friendly option for adjusting thresholds frequently, especially for users who are accustomed to working with data interactively.

Why the Other Options Are Less Suitable:

A. Threshold field with a filter pane: This option is less flexible and doesn't allow the same dynamic interaction as a variable and slider.

B. Shared spreadsheet and frequent app reloads: This approach is inefficient and would increase the load on the system unnecessarily. It is also less user-friendly for frequent threshold adjustments.

D. Bucket function: The Bucket function is not appropriate for this case, as it creates static groupings, which would not allow the user to adjust the threshold dynamically.

References for Qlik Sense Business Analyst:

Interactive Thresholds with Variables: Qlik Sense's variables and slider objects provide the best mechanism for dynamically controlling thresholds in a visualization.

Thus, introducing avariablefor the threshold and controlling it with avariable slideris the best solution, makingCthe correct 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.

To answer the two questions:

How many students are in the system?

What percentage of students have not yet attempted an exam?

The analyst needs to focus on theStudentIDfield, specifically in relation to theAttemptstable. This is because theAttemptstable captures all exam attempts made by students, and we can deduce which students have and have not made an attempt by examining the presence of StudentID values in this table.

Key Concepts:

Total Distinct Values: This provides the total number of unique students who have attempted exams. It helps identify how many students have made at least one attempt.

Subset Ratio: This compares the values ofStudentIDbetween theStudentstable and theAttemptstable. The subset ratio shows how many students in theStudentstable are represented in theAttemptstable. This ratio helps determine the percentage of students who have not yet attempted any exams.

Why the Other Options Are Less Suitable:

B. Non-null values and Subset ratio for the StudentID field in the Students table: Thenon-nullvalues in theStudentstable are not relevant to the question about exam attempts. The focus should be on whether theStudentIDis present in theAttemptstable.

C. Subset ratio and Present distinct values for the ExamID field in the Attempts table: This focuses on exams, not students. The question specifically relates to how many students have attempted exams.

D. Present distinct values and Density% for the ExamID field in the Exams table: This focuses on the number of exams and their density, which does not help in determining how many students have attempted or not attempted an exam.

References for Qlik Sense Business Analyst:

Subset Ratio and Distinct Counts: Qlik Sense’s data model viewer provides valuable metadata like thedistinct countof a field and itssubset ratiowhen compared to related fields in othertables. This is particularly useful for understanding relationships and gaps in the data, such as identifying students who have not yet made an exam attempt.

By focusing on theTotal distinct valuesandSubset ratiofor theStudentIDfield in theAttemptstable, the business analyst can easily determine the total number of students and the percentage who have not yet attempted an exam, makingAthe verified answer.

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.

In Qlik Sense, creatingMaster Itemsallows business analysts to define fields, dimensions, and measures that are used consistently across the app. This is particularly important for measures that will be used repeatedly. By defining these as master items, you ensure that all calculations are consistent and optimized for user experience and performance. This approach also supports drill-down capabilities while ensuring a responsive user experience.

Key Concepts:

Master Items: Master Items are reusable definitions for dimensions, measures, and visualizations. When you create a measure as a Master Item, it becomes available for use across different visualizations, ensuring consistency and reducing duplication of effort.

User Experience and Load Time: Using Master Items optimizes performance, as Qlik Sense caches the results of these items, reducing the need for recalculating complex measures each time they are used.

Why the Other Options Are Less Suitable:

A. Aggregate the data to the source period: While aggregation could reduce the data volume, it would limit the ability to drill down to the detailed levels required by the users.

C. Combine the various source fields in a calculated item in the Data manager: While you could create calculated fields, this method would be less efficient than defining measures in the Master Items library. Calculations done outside Master Items would need to be manually repeated in each visualization, leading to inconsistencies.

D. Combine the source fields and create additional fields in Excel: This would not optimize user experience or load time, as it relies on modifying source data outside of Qlik Sense and could lead to unnecessary data duplication and inefficiencies.

References for Qlik Sense Business Analyst:

Master Items Best Practices: Qlik Sense promotes the use of Master Items for consistent measure definition and reuse, as they improve performance and ensure consistency across multiple visualizations.

By creating a Master Item, the business analyst ensures a streamlined and efficient user experience, makingBthe best and verified option for this scenario.

Ascatter plotis the most appropriate visualization for analyzing the correlation betweenProduct Sales ($),Order Volume, andMargin %. 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, thescatter plotis the most effective visualization for analyzing the correlation between Product Sales, Order Volume, and Margin %, makingCthe correct answer.

For analyzing the relationship between Sales and Margin, ascatter plotis ideal, as it allows you to visualize the relationship between two measures (Sales and Margin) across various dimensions such as Customer or Product Category. Thefunnel chartis 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 ascatter plotand afunnel chartprovides the best solution, makingBthe correct answer.

To meet the requirement of controlling the number of products displayed in the bar chart, the business analyst should use aslider objecttied to a variable. The variable will store the number of products the user wants to display. In theAppearancesection of the bar chart's properties, the analyst can set the number of bars to acustom valueusing the variable, ensuring that the user can dynamically change the number of displayed products.

Key Concepts:

Slider Object: This provides a user-friendly way for users to adjust the number of products displayed in the bar chart.

Custom Bar Limitation: By setting the number of bars displayed to a custom value controlled by the variable, the business analyst ensures that the user can dynamically adjust how many products are shown.

Why the Other Options Are Less Suitable:

B. Use the variable to fix the limitation and add an input box: While this could work, sliders provide a better, more intuitive user experience than input boxes for adjusting values dynamically.

C. Use the variable to fix the limitation and add a slider: This is almost correct, but it misses the step of setting the number of bars to a custom value using the variable.

D. Add the slider object and set its value, but without custom bar settings: While adding a slider is correct, not setting the number of bars to custom using the variable means the user wouldn’t be able to dynamically control the number of displayed products.

References for Qlik Sense Business Analyst:

Dynamic Control with Variables and Sliders: Qlik Sense best practices recommend using sliders and variables to give users control over visualizations, particularly when it comes to dynamically limiting data displayed.

Thus, adding theslider objectand setting the number of bars to acustom valuecontrolled by the variable is the best solution, makingAthe verified answer.

The app is experiencing performance issues due to inefficient calculations in a master measure that processes the field TransactionName, which has a complex structure (e.g., "1_ABCDEFGHI_23454"). Let’s analyze the available options and whyOption Bis the best solution.

A. Ask the developer of the underlying database to change the structure of the field TransactionName.While modifying the data structure in the underlying database might improve performance, this approach is not ideal. It’s a time-consuming process that might not be feasible, especially when working with large datasets that have already been integrated into the Qlik Sense app. The performance improvement should focus on optimizing the Qlik app itself.

B. In the Data manager, use the Split function to split the field values with the underscore character as the separator. In the Data manager, use the Add calculated field function to multiply the 1st and the 3rd column of the split field. Reload the data.This is the most efficient approach. By using theSplit functionin the Data Manager to break down the TransactionName field based on the underscore separator, the data becomes more accessible for calculations. You can then create a calculated field that multiplies the first and third components of the split data (corresponding to the 1st part and the numeric identifier at the end). This reduces the need for complex string manipulation functions (e.g., Left, Right, Trim) within the master measure, which can be resource-intensive when applied to large datasets.

C. Change the master measure definition as follows: subfield( TransactionName, '',!) * subfield( TransactionName, '', 3)This option suggests using thesubfield() functionto split the string within the master measure itself. While this approach is valid, it doesn’t provide as significant a performance improvement compared to pre-processing the data in theData Manager. Calculating fields directly within the visualizations is more computationally expensive compared to handling it during the data load phase.

D. In the Data manager, use the Replace function to remove the middle part of the field TransactionName.TheReplace functionwould remove the middle section of the transaction name, but it doesn’t address the need to split the field for efficient multiplication. It would also result in a loss of important data that may be required for other analyses.

Key Qlik Sense Business Analyst References:

TheData Managerprovides powerful tools for transforming and optimizing data before it is used in visualizations. Pre-processing the data using functions likeSplitsignificantly reduces the load on front-end visualizations.

Splitting fields during the data load rather than in the master measures improves performance, especially in large datasets where string manipulation functions in visualizations can degrade performance.

Calculated fieldsallow analysts to create new expressions based on transformed data, ensuring that the app remains efficient while meeting analytical needs.

Thus, the correct solution is touse the Split function to separate the field values and then use a calculated field to multiply the required components, which enhances app performance.