Free Practice Questions for Qlik QSBA2022 Exam

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 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.

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.

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.

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.

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 other tables. 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 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.

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.

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 user can 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.

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 linechart 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.