QSBA2024 Practice Exam Questions with Answers Qlik Sense Business Analyst Certification Exam-2024 Certification

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 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.

The best solution for minimizing navigation clicks, maximizing screen real estate, and ensuring fast response times is to use acontainer object. A container object allows the business analyst to house multiple charts within a single visualization, making it easy for users to switch between them with minimal navigation. This also ensures that only one chart is rendered at a time, which improves screen response time.

Key Concepts:

Container Object: This feature allows multiple charts to be placed in one object, minimizing navigation clicks and maximizing screen real estate, as users can switch between charts within the same view.

Fast Response Time: Since only one chart is visible at a time, rendering performance is optimized, ensuring fast responses when switching between visualizations.

Why the Other Options Are Less Suitable:

A. Conditional show: This could lead to performance issues, as multiple charts would be rendered simultaneously, slowing down response time.

B. Single sheet with all charts: This would clutter the screen and reduce chart size, making it less optimal for user experience.

D. Several sheets with buttons for navigation: This increases the number of navigation clicks, which contradicts the requirement of minimizing navigation.

References for Qlik Sense Business Analyst:

Container Object for Multiple Visualizations: Qlik Sense recommends container objects when you need to show multiple charts with minimal navigation and maximum screen real estate.

Thus, using acontainer objectto host the required visualizations is the best solution, makingCthe verified answer.

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 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.

When loading data from an Excel file with more than 100 columns, where only columns with the suffix _c are relevant, the most efficient approach is to use theData Manager. The Data Manager provides a preview of the table being loaded, allowing the business analyst todeselect columnsthat do not have the _c suffix. This is a quick and straightforward method that avoids manual editing of the Excel file and allows the analyst to focus on the necessary columns.

Key Concepts:

Data Manager Preview: The Data Manager allows you to inspect and modify which columns will be loaded into the data model. The preview panel makes it easy to deselect columns that are not needed.

Efficient Data Loading: By using the Data Manager, the business analyst can avoid loading unnecessary columns, ensuring a cleaner and more manageable data model.

Why the Other Options Are Less Suitable:

A. Load all columns: This would load unnecessary columns, leading to a bloated data model with duplicates and irrelevant data.

B. Utilize filter functionality: While filtering could work, deselecting fields directly in the preview is more efficient and straightforward.

C. Edit the Excel file: Manually editing the Excel file is unnecessary and could lead to errors, especially when Qlik Sense provides tools to handle this within the platform.

References for Qlik Sense Business Analyst:

Data Manager for Field Selection: Qlik Sense recommends using the Data Manager to inspect and selectively load data fields, which is particularly useful when dealing with large datasets.

Thus,Dis the best solution because it allows for selective loading of relevant columns, making it the 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.

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.

The most effective way to control sheet access based on group assignment is to use theGroup fieldin theSection Access tableand apply it to theshow/hide conditionof the sheets. Each Sales Account ID is already mapped to a Group, so the business analyst can use this Group field to dynamically control which sheets are visible based on the user’s Group assignment. This ensures that each Sales Account only sees their respective Group's sheet.

Key Concepts:

Section Access with Groups: By incorporating the Group field into Section Access, the analyst can restrict sheet visibility based on group membership.

Show/Hide Condition: This feature in Qlik Sense allows certain sheets or objects to be displayed or hidden based on conditions, in this case, the user’s group.

Why the Other Options Are Less Suitable:

A. Sales Account ID as a filter: The Sales Account ID is used for data filtering but is not the appropriate condition for controlling sheet visibility.

B. Group as a filter on the sheet: While Group can be used as a condition, it must be managed through Section Access to ensure proper visibility control.

D. OSUser() function: While OSUser() can capture the user’s login information, using the Group field in Section Access is more efficient for controlling access to specific sheets based on group assignments.

References for Qlik Sense Business Analyst:

Show/Hide Sheets Based on Section Access: Qlik Sense supports the use of Section Access for controlling access to sheets based on user roles and group assignments.

Thus,Cis the most appropriate solution because it uses the Group field within Section Access to control sheet visibility, making it the correct answer.