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.

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.

ANetwork chartis the most suitable visualization for representing processes and tasks that have dependencies, such as projects with co-dependent tasks and subtasks. The network chart allows you to visualize relationships between nodes (in this case, tasks and subtasks) and can display them in a structured manner with lines connecting them based on their relationships. The colors of the boxes (or nodes) can be determined by the status of each project or task, which matches the requirements.

Key Concepts:

Network Chart: It’s designed for showing interconnections or relationships between various elements. It is ideal when tasks or processes have dependencies or subtasks that need to be visually represented with links between them.

Color Representation: In a Network Chart, you can easily apply colors to nodes based on specific criteria, such as the status of the task, making it easier for users to track project progress at a glance.

Why the Other Options Are Less Suitable:

A. Sankey chart: While Sankey charts are used to show flow and relationships between categories, they are better suited for representing flows of data or values between stages, not hierarchical or task-related dependencies.

B. Grid chart: A grid chart is used to display values in a matrix but does not provide the relational and hierarchical representation needed for tasks and subtasks.

C. Org chart: Org charts are useful for showing hierarchies but are more structured for organization personnel or roles rather than co-dependent tasks and workflows.

References for Qlik Sense Business Analyst:

Network Diagram: Network charts are widely used for visualizing complex relationships between entities, which aligns with the need to visualize tasks and subtasks in project management.

Thus, aNetwork chartprovides the best solution for visualizing tasks and subtasks with their dependencies, makingDthe 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.

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, theInsights Advisor Chatis the feature that allows users to interact with the app throughnatural language questions. This tool leverages Qlik's advanced AI and machine learning capabilities to interpret natural language queries and generate relevant insights, visualizations, or suggestions for analysis.

A. Advanced AuthoringAdvanced Authoring is a set of tools in Qlik Sense designed for creating detailed visualizations and reports, but it does not include natural language interaction capabilities. It is focused more on customization and precise design rather than conversational querying.

B. Story and BookmarksStorytelling and bookmarks in Qlik Sense are tools for narrative data presentations and saving specific states of analysis. They do not provide the ability to ask natural language questions or automatically generate insights.

C. Insights Advisor ChatInsights Advisor Chatis the correct answer. This feature allows users to interact with their data by typing natural language questions, which the system interprets to generate appropriate responses, including charts, KPIs, and other insights. It is designed to assist non-technical users by making data exploration more intuitive and accessible through natural language.

D. Associative EngineThe Associative Engine is the underlying technology that allows Qlik Sense to handle large datasets and perform associative searches across them. While it is powerful for data exploration, it does not provide a direct interface for natural language querying like Insights Advisor Chat does.

Key Qlik Sense Business Analyst References:

Insights Advisor Chatis a feature in Qlik Sense that empowers users to ask questions in natural language and get meaningful responses without needing to be data experts.

It is part of Qlik Sense’s broader set of augmented intelligence tools that enhance the user experience by providing guided insights and helping users discover relationships in data through natural language queries.

This feature simplifies data exploration for business users who might not be familiar with complex data querying techniques.

Thus, the feature that allows users to use natural language questions in Qlik Sense isInsights Advisor Chat.

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.

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.

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.

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.

TheMulti KPIobject is designed to display multiple key measures in a compact and visually appealing format, making it ideal for a dashboard that requires a minimal number of visualizations but must present multiple key metrics. By usingmaster visualizations, the business analyst ensures consistency and reusability across different sheets. This setup also allows for easy navigation through the app, as users can drill down into more detailed sheets when needed.

Key Concepts:

Multi KPI: This visualization allows multiple key performance indicators (KPIs) to be displayed in a single object, reducing the need for multiple charts or visualizations while ensuring that critical metrics are visible.

Master Visualizations: These ensure that KPIs are consistent across the app and can be reused as needed, helping to maintain a clean and efficient dashboard.

Why the Other Options Are Less Suitable:

B. Dynamic text and image linked objects: This could work for navigation, but it wouldn’t meet the requirement of displaying multiple key measures in a minimal number of visualizations.

C. Bookmark: A bookmark is used to save a particular state of selections but isn’t useful for showing multiple KPIs simultaneously.

D. Container: While containers can hold multiple visualizations, the Multi KPI object is more suited to displaying multiple key measures in a compact space.

References for Qlik Sense Business Analyst:

Multi KPI for Compact Dashboards: Qlik Sense recommends using Multi KPI objects when there is a need to display multiple key metrics in a minimalistic format.

Thus,Ais the best choice to meet the CEO's requirements, making it the correct answer.

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.