Free Qlik QSBA2022 Practice Exam with Questions & Answers | Set: 3

Acombo chartis 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, acombo chartprovides the most effective solution for showing both monthly sales values and the rolling 3-month summary, makingCthe 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.

To efficiently categorize support cases based on age (New, Aging, Beyond SLA) for use in multiple places across the dashboard, theBucket option in the Data Manageris the most efficient approach. Bucketing allows the business analyst to create new categories based on the values in an existing field (in this case, the age of support cases). Since the dataset is expected to grow, creating the categories directly within Qlik Sense ensures that the process is scalable without the need for external tools or extensive coding.

Key Concepts:

Bucket Function: This allows you to group numeric fields into predefined ranges or categories. The function is highly scalable, making it suitable for large datasets.

Efficiency: Creating a new field using Bucketing ensures that the categorization is done directly in the app, avoiding the need for external data sources or nested IF statements, which could impact performance.

Why the Other Options Are Less Suitable:

A. Ask the ServiceNow team to create the field: This would create a dependency on external teams and could delay the development process.

B. Create an Excel sheet: This adds unnecessary complexity and isn’t scalable as the dataset grows.

D. Write a master dimension with a nested IF statement: While this could work, it's less efficient for handling large datasets and could result in slower performance.

References for Qlik Sense Business Analyst:

Bucketing Data: Qlik Sense recommends using the Bucketing feature for creating predefined ranges or categories, especially when dealing with large datasets.

Thus, using theBucket optionto create a new field for categories is the most efficient solution, makingCthe correct answer.

The most effective way to control sheet access based on group assignment is to use theGroup fieldin theSection Access tableand apply it to theshow/hide conditionof the sheets. Each Sales Account ID is already mapped to a Group, so the business analyst can use this Group field to dynamically control which sheets are visible based on the user’s Group assignment. This ensures that each Sales Account only sees their respective Group's sheet.

Key Concepts:

Section Access with Groups: By incorporating the Group field into Section Access, the analyst can restrict sheet visibility based on group membership.

Show/Hide Condition: This feature in Qlik Sense allows certain sheets or objects to be displayed or hidden based on conditions, in this case, the user’s group.

Why the Other Options Are Less Suitable:

A. Sales Account ID as a filter: The Sales Account ID is used for data filtering but is not the appropriate condition for controlling sheet visibility.

B. Group as a filter on the sheet: While Group can be used as a condition, it must be managed through Section Access to ensure proper visibility control.

D. OSUser() function: While OSUser() can capture the user’s login information, using the Group field in Section Access is more efficient for controlling access to specific sheets based on group assignments.

References for Qlik Sense Business Analyst:

Show/Hide Sheets Based on Section Access: Qlik Sense supports the use of Section Access for controlling access to sheets based on user roles and group assignments.

Thus,Cis the most appropriate solution because it uses the Group field within Section Access to control sheet visibility, making it the 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.

To meet the requirement of dynamically changing the number of countries and cities displayed in the visualizations, the business analyst should usevariablesto control the number of countries and cities shown. By creating two variables (vCountry and vCity), the analyst can use sliders to allow the user to adjust the maximum number of countries (up to 10) and cities (up to 5 per country) that are displayed. These variables can then be applied to each visualization to control the displayed data.

Key Concepts:

Variables: Variables allow users to dynamically adjust values in Qlik Sense visualizations. In this case, sliders can be used to change the number of countries and cities displayed.

Slider Object: Adding a slider enables users to easily adjust the values of the variables vCountry and vCity in a user-friendly manner.

Why the Other Options Are Less Suitable:

B. Input field and dimension limitation: This option is unnecessarily complex and doesn't provide the same dynamic control as using variables and sliders.

C. Input field without sliders: While input fields could work, sliders offer a more intuitive way for users to adjust the values dynamically.

D. Sheet action: Setting a sheet action to limit the data displayed is less flexible and doesn't provide the same dynamic interaction as using variables and sliders.

References for Qlik Sense Business Analyst:

Dynamic Visualizations with Variables: Qlik Sense recommends using variables and interactive objects like sliders to give users control over dynamic data visualizations.

Thus, the most effective solution is to create variables and use sliders to dynamically control the number of countries and cities, makingAthe correct 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 andthird 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.

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 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.

In this case, we need to count how many unique rodents have made at least one attempt at any maze. Since the relationship between the Rodent table and the MazeEscapes table is a one-to-many relationship (each rodent may attempt several mazes), the best approach is to base the calculation on theMazeEscapestable, as it holds the actual records of rodent attempts.

By creating a new fieldRodentID_Counterin theMazeEscapestable, the analyst ensures that each rodent’s attempt is captured. Using theCount (Distinct RodentID_Counter)as the KPI expression then accurately counts each unique rodent that has made at least one attempt, without counting multiple attempts by the same rodent.

Key Concepts:

Distinct Count: The distinct count ensures that rodents who have made multiple maze attempts are only counted once.

MazeEscapes Table: This table holds the records of each attempt, making it the correct source for this KPI.

Why the Other Options Are Less Suitable:

B. Sum (RodentID_Counter) in the Rodent table: This would incorrectly sum the number of rodents rather than counting unique attempts, leading to inaccurate results.

C. Sum (RodentID_Counter) in the MazeEscapes table: Summing the counter would not account for the distinct rodents, leading to incorrect counting.

D. RodentID_Counter in the Rodent table: This would not correctly reflect the rodents that have made an attempt, as not every rodent in the Rodent table may have attempted a maze.

References for Qlik Sense Business Analyst:

Distinct Count in KPI: It is best practice to use Count(Distinct ...) when working with KPIs that require unique counts, such as counting distinct rodents in this scenario.

Thus,Ais the verified answer because it ensures that each rodent is counted once, based on their attempts in the MazeEscapes table.