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.

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.

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.

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.

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.

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.

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 this scenario, the VP of Sales wants to see the total sales for the year 2022regardless of selections. This requirement is best handled usingSet Analysisin Qlik Sense. The key to achieving this is using the set identifier 1, which ignores the user's selections and ensures the calculation is based on the entire dataset. The expression Sum( { 1 < year = { '2022' } > } Sales) calculates the sum of sales for the year 2022, irrespective of any other selections made in the app.

Key Concepts:

Set Identifier 1: This identifier ensures that the calculation is performed on the entire dataset, ignoring any selections or filters applied by the user.

Year Filtering: The expression < year = { '2022' } > ensures that only sales from the year 2022 are included in the calculation.

Why the Other Options Are Less Suitable:

A. Sum( { < year = '2022' > } Sales): This is incorrectly formatted, and the pipe (|) symbol should not be used in this context.

B. Sum( { $ < year = { '2022' } > } Sales): The $ set identifier respects the current selections, which is not what is needed in this case, as the VP wants the value to be shown regardless of selections.

D. Sum( 1 { < year = { '2022' } > } Sales): The placement of 1 is incorrect in this expression.

References for Qlik Sense Business Analyst:

Set Analysis: Qlik Sense's Set Analysis allows analysts to control what data is used in a calculation, regardless of user selections. The set identifier 1 ensures that selections are ignored, which is essential for showing fixed data such as total sales for a specific year.

Thus, the correct expression to show the total sales for 2022, regardless of user selections, isC.

TheBar chartis used multiple times across various sheets, which makes it a good candidate to be added to theMaster Items library. Master items are reusable components that can be added to multiple visualizations across different sheets without needing to recreate them. Since the bar chart will be reused multiple times, adding it to the Master Items ensures consistency and reusability.

Key Concepts:

Master Items: These are predefined dimensions, measures, or visualizations that can be reused across multiple sheets in an app, ensuring consistency and reducing development time.

Why the Other Options Are Less Suitable:

A. Container: The container is only used once in this scenario, so it doesn’t need to be a master item.

B. KPI: The KPI is only used once, so it does not require master item status.

D. Treemap: The treemap is only used once in a container, so it doesn’t need to be a master item.

References for Qlik Sense Business Analyst:

Master Items for Reusability: Qlik Sense recommends adding frequently used charts or dimensions to the master items for easy reuse and consistency.

Thus, thebar chartis the best choice for adding to the master items, 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.

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 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.