QSBA2024 Questions and Answers

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.

TheDensityvalue in the Data Model Viewer provides a measure of how "dense" or "sparse" a field is in terms of data completeness. A higher density value means fewer nulls, while a lower value indicates more nulls. By checking the density value for each field, the business analyst can determine the percentage of non-null values, which is critical for understanding data quality and completeness.

Key Concepts:

Density Value: This is a measure in Qlik Sense that indicates the proportion of non-null values in a field. A field with a high density is mostly populated, while a lower density indicates a high proportion of null values.

Data Model Viewer: This tool allows analysts to inspect the structure and quality of data fields, including metrics such as density.

Why the Other Options Are Less Suitable:

B. Preview Panel: While the Preview Panel shows sample data, it does not provide a comprehensive measure of null values and is more suited for a quick glance rather than detailed analysis.

C. Tags fields with $null: This would show if the field contains any nulls, but it wouldn’t quantify the level of nulls.

D. Subset Ratio: The subset ratio compares values across related tables, not null values within individual fields.

References for Qlik Sense Business Analyst:

Data Quality in Qlik Sense: Using theDensityvalue is the best way to assess the proportion of null values in a field, making it ideal for the business analyst to understand the completeness of the data.

Thus,Ais the correct answer because the density value provides the required insight into the level of nulls in each field.

Storytellingin Qlik Sense allows business users to create dynamic presentations based on data insights. This feature is ideal for executives like the VP of Finance who need to share financial insights in meetings. Storytelling allows users to create guided stories from data visualizations, offering a customizable solution that can be tailored to the monthly meeting agendas.

Key Concepts:

Storytelling: This feature enables users to create data-driven stories with snapshots from Qlik Sense visualizations, allowing for dynamic, customized presentations that can be updated as data changes.

Customizable: The VP of Finance can customize the presentation each month to focus on relevant financial metrics and insights.

Why the Other Options Are Less Suitable:

B. Insight Advisor Chat: While helpful for querying data interactively, this option is not suited for presenting data in a structured, presentable format to executives.

C. Action Buttons: Action buttons are used for navigating or interacting within apps, but they are not relevant for creating presentations.

D. Bookmarks: Bookmarks save specific selections, but they don’t provide the dynamic, presentable format needed for meetings.

References for Qlik Sense Business Analyst:

Storytelling in Qlik Sense: This feature is often recommended for creating interactive, data-driven presentations, especially for executive-level meetings.

Thus,Storytellingoffers the most effective solution for presenting financial data in a customizable format, makingAthe correct 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.

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.

To make the price ranges dynamically adjustable by the application users, a variable input object is the best approach. The business analyst can define a variable that stores the range value, which users can modify directly through a variable input control. This method allows users to change the price ranges interactively, giving them control over the ranges used in the analysis.

Key Concepts:

Variable Input Object: This object allows users to interact with and modify the values of predefined variables directly within a Qlik Sense sheet, which can then be used to adjust calculations dynamically, such as defining custom ranges.

Configurable by Users: This approach gives end-users the flexibility to modify the visualization based on their specific needs without requiring backend changes or reloading the app.

Why the Other Options Are Less Suitable:

B. Create a calculated field in Data manager, using the Class() function: The Class() function is useful for creating static price ranges, but it does not allow for user interaction or dynamic updates to the ranges.

C. Load an independent source file to contain the user-defined boundary values: While this could provide configurable ranges, it's unnecessarily complex and would require more management, and it’s not as user-friendly as using a variable.

D. Create the price range dimension using the Buckets feature in Data manager: Similar to the Class() function, this would create static groupings, which wouldn’t be dynamically adjustable by the user.

References for Qlik Sense Business Analyst:

Dynamic Controls with Variables: Qlik Sense provides the ability to create variable input objects that allow users to control how visualizations behave dynamically. This feature is highlighted in Qlik Sense’s Business Analyst best practices when making interactive applications.

By using a variable and a variable input object, the business analyst enables user interactivity and customization, makingAthe correct choice.

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.

To meet the needs of both the internal analyst team and the sales team, the best solution is to createtwo separate apps: one designed specifically for mobile use and another for internal use. Mobile devices require different UI considerations, such as simpler, touch-optimized layouts, while the internal team can benefit from a more detailed app optimized for desktop use. Designing separate apps ensures that both teams have a tailored experience that suits their specific devices and use cases.

Key Concepts:

Mobile Optimization: Mobile devices require apps that are streamlined and optimized for smaller screens, while internal users on desktop computers can handle more complex layouts and detailed reports.

Separate Apps: Creating separate apps ensures that each team gets the best user experience tailored to their needs.

Why the Other Options Are Less Suitable:

A. One app with a specific extension for mobile users: While extensions can provide some mobile functionality, they don’t offer the flexibility and optimization needed for a fully mobile-friendly experience.

C. A mashup with various objects: A mashup may provide flexibility, but it could be overly complex for this requirement and wouldn’t necessarily offer an optimal mobile experience.

D. One app with various objects: This could complicate the user experience for both teams, as mobile users may struggle with objects that are not optimized for their devices.

References for Qlik Sense Business Analyst:

Mobile vs. Desktop App Design: Qlik Sense recommends optimizing apps for specific devices to ensure the best user experience for both desktop and mobile users.

Thus,Bis the correct answer because it provides the best solution for both the mobile sales team and the internal analyst team, making it the verified 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.

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.