Qlik QSBA2024 Qlik Sense Business Analyst Certification Exam-2024 Exam Practice Test

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.

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.

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.

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.

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.

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.

To recreate the dashboard image provided by the HR Director, the following charts are needed:

Map chart: To show the geographical representation of office capacity.

Org chart: To show the company employee structure.

Line chart: To show company retention over time.

Bar chart: To show average employee salary by region.

Key Concepts:

Map Chart: Used to visualize geographical data, such as office capacity across different locations.

Org Chart: Ideal for displaying hierarchical structures, such as the employee structure of a company.

Line Chart: Best suited for showing trends over time, such as employee retention.

Bar Chart: A good choice for comparing salaries across regions.

Why the Other Options Are Less Suitable:

A. Sankey chart: This chart is used for flow or process analysis, not employee structure.

B. Network chart: Network charts show relationships but are not ideal for hierarchical structures like an org chart.

C. Grid chart and KPI chart: These charts are not well-suited for the types of data required in this scenario.

References for Qlik Sense Business Analyst:

Chart Selection for HR Dashboards: Qlik Sense provides various visualization options, and selecting the correct chart for each type of data is essential for accurate and clear representation.

Thus, the correct combination of charts isD—Map chart, org chart, line chart, and bar chart—making it the verified answer.

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.

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.

In Qlik Sense,default bookmarksallow a set of selections to be applied automatically whenever the app is opened. By creating a bookmark and setting it as the default, the business analyst ensures that the required selections are applied every time the app is opened, which meets the requirement of consistently applying the same selections for all users.

Key Concepts:

Default Bookmark: A default bookmark automatically applies the saved selections when an app is opened, ensuring consistency without manual input from users.

Bookmarking: This feature allows users to save specific selections or states of a dashboard for later use.

Why the Other Options Are Less Suitable:

A. Section Access: Section Access controls data access and security, not default selections.

B. Mashup with API: While this could technically work, it's unnecessarily complex and requires custom coding.

C. Sheet Action: A sheet action could apply a bookmark but would not ensure that the selections are applied at the time of app opening.

References for Qlik Sense Business Analyst:

Default Bookmark for Predefined Selections: This feature is commonly used to ensure that specific selections are always applied when an app is opened.

Thus,Dis the best solution for applying default selections, making it the 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.

For this scenario, using abar chart,scatter plot, andhistogramprovides the best coverage of the requirements. Thebar chartis ideal for comparing the sales performance of the top 10 sales representatives. Thescatter plotis used to analyze the relationship between margin percentage and total sales by product category. Thehistogramis excellent for visualizing the distribution of sales amounts.

Key Concepts:

Bar Chart: Perfect for comparing categorical data, such as sales amounts across different sales representatives.

Scatter Plot: Ideal for exploring relationships between two variables, such as margin percentage and total sales.

Histogram: Provides a clear visualization of the distribution of a continuous variable, such as sales amounts.

Why the Other Options Are Less Suitable:

B. Treemap, Container, and Distribution plot: A treemap is less effective for comparing individual sales reps, and a container does not provide a clear visualization on its own.

C. Bar chart, Line chart, and Scatter plot: A line chart is not needed in this case, as it is best for showing trends over time, which is not required here.

D. Treemap, Box plot, and Histogram: A box plot is more suited for showing statistical distributions (e.g., quartiles), which is unnecessary in this case.

References for Qlik Sense Business Analyst:

Data Exploration: Bar charts, scatter plots, and histograms are among the most commonly recommended visualizations for comparing performance, analyzing relationships, and viewing distributions in Qlik Sense.

Thus, the combination of abar chart,scatter plot, andhistogramoffers the most comprehensive solution, 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.

In the provided exhibit, the movie analyst filters by theLength Rangefield and notices a hyphen (“-”), which typically indicatesmissing datain Qlik Sense. When the analyst selects this hyphen, it filters out the rows where no data exists for the Length Range field.

Let’s review the options:

A. Six movies in the source data contain illegal characters for the Length Range field.This statement is incorrect. The hyphen (“-”) is not an indicator of illegal characters. In Qlik Sense, it usually representsnull values or missing data, not improperly formatted data.

B. Movies at the start of the 20th century often varied in length.This answer is not relevant to the specific observation of the hyphen in the Length Range field. The hyphen does not provide insights into the variation of movie lengths; it indicates missing data.

C. All movies from the 1920s or 1930s contain no data for Length Range.While the screenshot shows some movies from different decades, we cannot definitivelyconclude that all movies from a particular era are missing the Length Range data. The hyphen indicates that some movies across various years are missing data, but this does not apply to all movies from the 1920s or 1930s.

D. The source data for six movies is missing a Length Range.This is the correct interpretation. The hyphen in theLength Rangecolumn indicates that these six movies lack data for this field. Selecting the hyphen allows the analyst to identify movies with missing values in the Length Range field.

Key Qlik Sense Business Analyst References:

Hyphen (“-”) in Qlik Sensetypically represents null or missing values in a field.

Filter panesin Qlik Sense allow users to quickly see where data may be incomplete or missing, and selecting these null values provides immediate insight into which records are affected.

Thus, the correct determination is thatthe source data for six movies is missing a Length Range.

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.