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

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.

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 large datasets, such as the one containing over a billion rows in this scenario, loading the entire dataset can be time-consuming, especially during the development phase. Qlik Sense provides aFilter dataoption in the Data Manager, which allows business analysts to work with a subset of the data during development. This is particularly useful for rapidly prototyping the application design.

Key Concepts:

Filter Data Option: This feature in Qlik Sense allows the analyst to load a smaller sample of the dataset for analysis and development purposes. By filtering out unnecessary rows, the business analyst can quickly build and prototype the application without waiting for the full dataset to load. Once the design is finalized, the full dataset can be reloaded.

Prototyping with Reduced Data: It’s often more efficient to work with a smaller dataset during the design phase. This allows for faster iterations and design cycles, especially when working with large datasets.

Why the Other Options Are Less Suitable:

A. Split the dataset and create a normalized star schema of associated tables: This would involve complex data modeling that is not necessarily related to the immediate need of reducing the size of the dataset for prototyping. While star schemas can optimize data models, it’s not the quickest way to reduce the number of rows for initial testing.

B. Deselect text columns with unique data values to reduce the memory footprint: This may reduce the memory usage but won't necessarily address the issue of reducing the number of rows. Also, the text columns might be important for the analysis and should not be removed without careful consideration.

D. Truncate text fields longer than 256 characters to create preview fields: Truncating text fields will not significantly reduce the dataset size or the load time. It may also result in losing critical information, which is not ideal for prototyping.

References for Qlik Sense Business Analyst:

Rapid Prototyping: Qlik Sense encourages rapid development of applications by allowing business analysts to work with subsets of the data. The Filter Data option is an important tool for managing large datasets efficiently.

Data Manager Tools: The Data Manager in Qlik Sense provides several tools for reducing the dataset size, and filtering is one of the key options for improving performance during development.

Using theFilter dataoption allows the business analyst to focus on a smaller subset of data, enabling quicker prototyping and iteration, which makes optionCthe most effective solution.

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 InternEmp table contains information about temporary employees (interns), and the Employees table contains regular employee data. To properly link these two tables, the business analyst needs to create an association between theEmpIDin theInternEmptable and theEmployeeIDin theEmployeestable. This will ensure that the two tables are correctly associated based on the employee identifiers, allowing the system to relate both tables in the data model.

Key Concepts:

Association: Qlik Sense automatically suggests associations between tables based on field names. By linkingEmpIDfrom InternEmp withEmployeeIDfrom Employees, the tables can be properly related in the data model.

Association View: The association view in Data Manager helps visualize how tables are connected and suggests appropriate links between tables based on common fields.

Why the Other Options Are Less Suitable:

A. Create a concatenated key: Concatenation is unnecessary for this scenario since the data model relies on direct associations between keys.

B. Concatenate the tables: Concatenating the InternEmp table into the Employees table would combine the records, but it’s not appropriate since the two tables should remain separate entities.

C. Force an association between InternEmp and Orders: There’s no need to associate InternEmp with Orders directly since the focus is on employees and interns.

References for Qlik Sense Business Analyst:

Field Associations in Qlik Sense: Properly associating fields between tables is crucial for building a clean and efficient data model in Qlik Sense.

Thus, creating an association betweenEmpIDandEmployeeIDis the best approach, makingDthe correct answer.

The banking dashboard requires several KPIs and visualizations based on current year (CY) and last year (LY) revenue, as well as cost and customer satisfaction. To build the required measures, the fieldsCY Revenue, LY Revenue, and CY Costare necessary because they provide the comparison between the current and previous year, as well as cost-related data for the specific calculations.

Key Concepts:

KPI for CY vs LY Revenue: This requires both CY Revenue and LY Revenue fields.

Scatter Plot for Cost vs Revenue: This comparison requires both CY Revenue and CY Cost to create the necessary relationship in the scatter plot.

Treemap for Customer Satisfaction: In addition to the customer satisfaction rating, the field CY Revenue would likely be used for additional insights by region.

Table with CY Cost: The table requires CY Cost data along with other relevant fields like record number, financial instrument, and bank.

Why the Other Options Are Less Suitable:

B. CY Revenue, LY Revenue, Cost: While this covers the revenue fields, it does not specifically includeCY Cost, which is needed for the table and scatter plot.

C. Revenue and Cost: This option is too general and does not distinguish between current year and last year revenue, which is essential for the KPI.

D. Revenue and CY Cost: This does not include LY Revenue, which is required for the KPI.

References for Qlik Sense Business Analyst:

Comparison Measures in Qlik Sense: In Qlik Sense, comparisons across time periods like CY and LY require specific fields to calculate accurate insights, and it’s essential to ensure the appropriate fields are included for each visualization.

Thus,Aprovides the correct set of fields for the required dashboard, making it the verified answer.

In Qlik Sense, when leadership requests a high-level summary such as thetotal cost of delivery overall, the most efficient way to present this information is by using aKPI object. The KPI object is specifically designed to display a single, important metric in a simple and clear format.

A. Use the line chart to add up each month-year to get to the number required.This option is not efficient because it requires manual effort to add up the values from the line chart for each period. Additionally, this method is prone to human error and would be time-consuming during a presentation.

B. Create a KPI object that shows the total cost of delivery.The most appropriate action here is to use aKPI objectto display the overall total cost of delivery. A KPI in Qlik Sense is specifically designed to display single, aggregate measures in a clean and concise way, making it the perfect choice for presenting high-level summaries to leadership.

C. Adjust the line layer on the map to reflect the cost of delivery.While it is possible to adjust the map, the map is primarily used for spatial analysis. Modifying it to reflect the overall cost of delivery would not be as intuitive or effective as using a KPI object. Additionally, it could lead to unnecessary clutter and confusion for the audience.

D. Select all products in the scatter plot to see the total delivery cost.Selecting all products in the scatter plot would not give the desired result because the scatter plot is designed to show relationships between variables (cost of delivery and time-to-deliver). It’s not ideal for displaying aggregate values like total cost.

Key Qlik Sense Business Analyst References:

KPI objectsare ideal for presenting single, key metrics such as the total cost of delivery. They provide a straightforward, visually clear representation of high-level performance indicators.

Best practices in dashboard developmentemphasize the importance of creating specific visualizations that address both granular and high-level data needs. KPI objects fulfill the need for high-level summaries, particularly in leadership presentations.

Thus, the best way to show the total cost of delivery to leadership is tocreate a KPI object.

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 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.

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.