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

To inform a company director when a threshold is breached,Alertingis the most appropriate feature. Qlik Sense allows users to set up automated alerts based on specific conditions or thresholds. Thesealerts can be configured to notify users when certain criteria are met, making it ideal for keeping the director informed without requiring them to constantly check the application.

Key Concepts:

Alerting: This feature allows users to set conditions (such as when a sales or performance threshold is breached) and automatically send notifications to the relevant individuals.

Automated Notifications: Alerting ensures that the director is notified promptly and automatically when a critical threshold is reached.

Why the Other Options Are Less Suitable:

A. Weekly PDF report: A weekly report would not provide real-time notifications, which are necessary when thresholds are breached.

B. Storytelling: Storytelling is used for presentations, not for monitoring thresholds.

D. Bookmark: A bookmark only saves a particular selection or view, and cannot send notifications when a condition is met.

References for Qlik Sense Business Analyst:

Alerting in Qlik Sense: Qlik Sense’s alerting functionality is designed to notify users when specific conditions are triggered, making it ideal for scenarios where timely notifications are critical.

Thus, usingAlertingis the best solution to notify the director when a threshold is breached, makingCthe verified answer.

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.

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 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.

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 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.

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.

In Qlik Sense, when dealing with inconsistent naming conventions across different systems or divisions (like the variation in country names), the best practice is to standardize the data during the loading process. Using alookup tableis the most efficient approach to achieve this. This involves loading a separate table that contains all variations of a country name along with the standardized version. During the load process, Qlik Sense can then map the varying names to a common value.

Key Concepts:

Lookup Table: A lookup table contains key-value pairs where different versions of a data element (like country names) are mapped to a single standard value. In this case, the lookup table could have entries like USA, U.S.A., US all mapped to United States of America.

Data Standardization: This is crucial in ensuring consistent analysis across datasets. By converting variations of country names into a single consistent value, the business analyst ensures that all data visualizations and analysis will treat "USA", "US", etc., as the same entity.

Why the Other Options Are Less Suitable:

A. Create a calculated master dimension expression: While this could theoretically work by creating a calculated expression to handle variations, it's not scalable or maintainable, especially as new variations in country names could appear in future data loads.

C. Cleanse the source text file prior to loading: This option would require modifying the raw data files manually, which is time-consuming and not sustainable if data is frequently updated or if the number of variations is extensive.

D. Use the Replace option in Data manager: The Replace option in the Data Manager could work on a small scale, but it requires manual intervention each time, which is not efficient or sustainable when new data is loaded. Also, it’s more useful for one-off corrections than for handling systemic issues across multiple data loads.

References for Qlik Sense Business Analyst:

Data Modeling Best Practices: Lookup tables are a common approach to resolve issues of inconsistent data across multiple sources. They ensure that data is consistently represented in visualizations and reduce the need for manual intervention.

Data Cleansing During Loading: Qlik Sense allows for transformation and data cleansing during the data load process. A lookup table is part of this capability and ensures that the data loaded into the app is clean and consistent.

Using a lookup table is the most scalable and maintainable approach to standardizing country names in this scenario, which is why optionBis the verified solution.

In scenarios where a customer needs to standardize colors across multiple apps and be able to update them quickly, usingvariablesin combination with aninclude statementis 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 aninclude 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:

Variablesare widely used in Qlik Sense for managing repeated expressions or values like colors. They can be defined once and reused throughout the app.

Include statementsallow 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 tocreate all color expressions as variables in a text file and load them into each app using an include statement.

Ascatter plotis the best choice for visualizing outliers, clustering, and products that are above the median sales volume. Scatter plots are excellent for showing relationships between two variables (like sales volume and margin %) while providing the ability to highlight outliers. By usingK-Means clusteringto color the products, the business analyst can visually group similar products. Additionally, adding amedian sales volume reference linemakes it easy to identify which products are above or below the median.

Key Concepts:

Scatter Plot: This visualization is ideal for detecting outliers and understanding the distribution and clustering of data points.

K-Means Clustering: This technique groups similar data points (products) based on their values, which helps to identify patterns visually.

Median Reference Line: Adding a reference line for median sales volume ensures that the analyst can easily see which products are performing above or below the median.

Why the Other Options Are Less Suitable:

A. Pivot table: While a pivot table could show aggregated data, it is not as effective for visualizing outliers or clustering as a scatter plot.

B. Treemap: A treemap can show hierarchical relationships but is not as effective for identifying clusters or outliers.

C. Combo chart: A combo chart is not as well-suited for visualizing clustering and outliers as a scatter plot.

References for Qlik Sense Business Analyst:

Outliers and Clustering Visualization: Qlik Sense recommends scatter plots for visualizing relationships between two measures and for detecting outliers and clustering in the data.

Thus, creating ascatter plotwith K-Means clustering and a median sales volume reference line is the best approach, makingDthe verified 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.

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.