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Qlik QSBA2024 認定試験の出題範囲：
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質問 # 21
A dashboard developer finishes creating a supply chain analysis app and is presenting it to leadership for review. The landing page shows four visualizations including:
* Bar chart showing available supply by product category
* Line chart showing total cost of deliveries to the warehouse by month-year
* Scatter plot showing cost of delivery and time-to-deliver by product
* A map that shows the volume of delivery from suppliers to warehouses using a line layer Leadership asks the developer how they can see the total cost of delivery overall. How can the analyst show this information to leadership?
- A. Select all products in the scatter plot to see the total delivery cost
- B. Use the line chart to add up each month-year to get to the number required
- C. Create a KPI object that shows the total cost of delivery
- D. Adjust the line layer on the map to reflect cost of delivery
正解：C
解説：
In Qlik Sense, when leadership requests a high-level summary such as the total cost of delivery overall, the most efficient way to present this information is by using a KPI 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 a KPI object to 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 objects are 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 development emphasize 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 to create a KPI object.
質問 # 22
An app needs to load a few hundred rows of data from a .csv text file. The file is the result of a concatenated data dump by multiple divisions across several countries. These divisions use different internal systems and processes, which causes country names to appear differently. For example, the United States of America appears in several places as 'USA', 'U.S.A.', or 'US'.
For the country dimension to work properly in the app, the naming of countries must be standardized in the data model.
Which action should the business analyst complete to address this issue?
- A. Cleanse the source text file prior to loading
- B. Use the Replace option in Data manager
- C. Load a lookup table to convert values
- D. Create a calculated master dimension expression
正解：C
解説：
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 a lookup table is 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 option B is the verified solution.
質問 # 23
Exhibit.
Refer to the exhibit.
An app is being developed at a university to monitor student exam attempts- Three core tables are loaded into the app for Students, Exams, and Attempts. Students can attempt the same exam multiple times.
Before building any visualizations, the business analyst needs to know:
* How many students are in the system
* What percentage of students have not yet attempted an exam
Which metadata should the analyst focus on to answer these questions?
- A. Non-null values and Subset ratio for the StudentID field in the Students table
- B. Subset ratio and Present distinct values for the ExamID field in the Attempts table
- C. Total distinct values and Subset ratio for the StudentID field in the Attempts table
- D. Present distinct values and Density% for the ExamID field in the Exams table
正解：C
解説：
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 the StudentID field, specifically in relation to the Attempts table. This is because the Attempts table 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 of StudentID between the Students table and the Attempts table. The subset ratio shows how many students in the Students table are represented in the Attempts table. 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: The non-null values in the Students table are not relevant to the question about exam attempts. The focus should be on whether the StudentID is present in the Attempts table.
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 the distinct count of a field and its subset ratio when 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 the Total distinct values and Subset ratio for the StudentID field in the Attempts table, the business analyst can easily determine the total number of students and the percentage who have not yet attempted an exam, making A the verified answer.
質問 # 24
A company CFO has requested an app that contains visualizations applicable to analyzing the finance dat a. Each regional finance team will analyze their data and should only have access to the data in their region. The app must contain a high-level sheet that navigates to relevant detail sheets.
Which features support a logical design structure?
- A. A dashboard with regional bookmarks
- B. A pivot table that filters by region
- C. A dashboard of KPIs and section access
- D. A Multi KPI with set analysis
正解：C
解説：
To fulfill the CFO's request for an app that allows each regional finance team to access only their data while navigating from a high-level sheet to detail sheets, the combination of a dashboard of KPIs and Section Access is ideal. A dashboard of KPIs provides high-level insights, and Section Access ensures that users from different regions can only see the data relevant to their region. Section Access allows for controlled access to data, ensuring data security and segregation.
Key Concepts:
Dashboard of KPIs: A dashboard displaying key performance indicators (KPIs) gives a high-level overview of financial data, allowing users to quickly assess critical metrics.
Section Access: This Qlik Sense feature controls data access based on user roles, ensuring that users only have access to the data relevant to their region.
Why the Other Options Are Less Suitable:
B . Pivot table: A pivot table is useful for detailed analysis but not suitable for designing a navigation structure or controlling access to data by region.
C . Multi KPI with set analysis: While set analysis can filter data, it doesn't control access at the regional level as effectively as Section Access.
D . Dashboard with regional bookmarks: Bookmarks are user-specific and do not offer security or access control, which is required in this scenario.
References for Qlik Sense Business Analyst:
Section Access for Regional Data Control: Qlik Sense recommends Section Access for managing data access when different users need to see only specific subsets of data.
Thus, A is the best solution because it combines high-level KPIs with robust data access controls using Section Access, making it the correct answer.
質問 # 25
The sales manager is investigating the relationship between Sales and Margin to determine if this relationship is linear when choosing the dimension Customer or Product Category.
The sales manager wants to have the potential percentage Sales for each Stage (Initial to Won) of the sales process.
Which visualizations will meet these requirements?
- A. Distribution plot: Alternative measures Sales and Margin, Alternatives dimensions Customer or Product category Bar chart: Dimension Stage, Measure Sales
- B. Scatter plot: Measures X-axis Sales and Y-axis Margin, Dimensions Customer or Product category Bar chart: Dimension Stage, Measure Sales
- C. Scatter plot: Measures X-axis Sales and Y-axis Margin, Alternative dimensions Customer or Product category Funnel chart: Segments Stage, Width Sales
- D. Combo chart: Measures Sales and Margin, Dimensions Customer or Product category Pie chart: Dimension Stage, Measure Sales
正解：C
解説：
For analyzing the relationship between Sales and Margin, a scatter plot is ideal, as it allows you to visualize the relationship between two measures (Sales and Margin) across various dimensions such as Customer or Product Category. The funnel chart is perfect for visualizing stages in a sales process, as it shows how sales progress from the initial stage to the final (Won) stage, with the width of each segment representing the total sales for each stage.
Key Concepts:
Scatter Plot: This type of chart is specifically designed to visualize the correlation or relationship between two measures, making it ideal for analyzing Sales versus Margin across different dimensions.
Funnel Chart: This chart is particularly suited for visualizing the sales stages, as it visually demonstrates the proportion of sales moving through each stage of the sales funnel.
Why the Other Options Are Less Suitable:
A . Scatter plot and Bar chart: While a scatter plot is correct for analyzing Sales and Margin, a bar chart won't adequately represent the different stages of the sales process as effectively as a funnel chart.
C . Combo chart and Pie chart: A combo chart could potentially work, but it would not show the relationship between Sales and Margin as clearly as a scatter plot. A pie chart is also less effective for representing stages in a sales funnel.
D . Distribution plot and Bar chart: A distribution plot does not effectively show the relationship between two measures, and a bar chart isn't the best choice for visualizing the stages of a sales process.
References for Qlik Sense Business Analyst:
Scatter Plot for Relationships: This chart type is highly recommended when exploring relationships between two continuous variables, such as Sales and Margin.
Funnel Charts: These are ideal for visualizing how data moves through various stages of a process, such as sales stages, from initial engagement to final sale.
Therefore, the combination of a scatter plot and a funnel chart provides the best solution, making B the correct answer.
質問 # 26
In the 'Sales By Product' bar chart, a customer wants to highlight a specific product bar that includes a dynamic label. The label will only be visible when conditions are met. Which feature should the business analyst add to the bar chart?
- A. A Dimension reference line add-on
- B. A Color By Expression property under Appearance
- C. An Alternative dimension with a calculation
- D. A reference line add-on under Properties
正解：B
解説：
To dynamically highlight a specific product bar in a bar chart based on conditions, the best approach is to use the Color By Expression feature under the Appearance settings in Qlik Sense. This feature allows you to apply conditional formatting to bars, changing their color dynamically based on expression logic.
A . A Color By Expression property under Appearance
This is the correct answer. The Color By Expression property allows the business analyst to dynamically color bars in the chart based on specific conditions. The expression can be set to highlight a specific product bar only when certain conditions are met, and the color can be customized to make it stand out.
B . A Dimension reference line add-on
Dimension reference lines are used to show thresholds or important values along the axes, but they do not dynamically color the bars or add conditional labels to them. This would not achieve the desired effect.
C . An Alternative dimension with a calculation
Alternative dimensions allow users to switch between different dimensions in the same chart, but they do not provide dynamic highlighting or conditional visibility for labels.
D . A reference line add-on under Properties
Reference lines are used to mark specific values or thresholds in a chart, but they do not interact with the dynamic coloring or visibility of labels on individual bars.
Key Qlik Sense Business Analyst References:
Color By Expression is a powerful feature in Qlik Sense that allows dynamic customization of chart colors based on expressions, making it ideal for highlighting specific data points or conditions.
This feature provides great flexibility in creating visually engaging and interactive charts that respond to changes in the underlying data or user selections.
Thus, the correct way to highlight a specific product bar with a dynamic label is to use Color By Expression under Appearance.
質問 # 27
A business analyst needs to create two side-by-side charts for a sales department with the following data:
* Number of orders
* Name of the customer
* Percentage of margin
* Total sales
The charts use a common dimension, but each chart has different measures. The analyst needs to create a color association between the two charts on the dimension values.
Which action should the business analyst take?
- A. Define the color values in the master measures and use the color library
- B. Use the Fieldlndex function to set the colors by expression for each dimension value
- C. Select 'By Dimension' and 'Persistent colors' in the Colors property panel
- D. Use nested IF statements to set the colors by expression for each dimension value
正解：C
解説：
In Qlik Sense, the 'By Dimension' and 'Persistent colors' options in the Colors property panel ensure that the same dimension values have the same color across multiple charts. This is especially useful when you have two or more side-by-side charts sharing a common dimension, like customer names in this case. Persistent colors guarantee consistency in color assignment, helping users visually track the same dimension across different visualizations.
Key Concepts:
By Dimension: This option ensures that each unique value of a dimension (e.g., customer name) gets a distinct color across all charts that use this setting.
Persistent Colors: This feature ensures that the colors remain the same between charts, making the visual comparison across charts easier for the users.
Why the Other Options Are Less Suitable:
A . Use nested IF statements to set the colors by expression for each dimension value: While this would work, it would be unnecessarily complex to maintain and manage, especially with many dimension values.
B . Define the color values in the master measures and use the color library: This would only apply if the goal was to set colors based on measures, not dimensions. In this case, dimension consistency is required, not measure-based coloring.
D . Use the FieldIndex function to set the colors by expression for each dimension value: This would involve writing complex expressions that would not be as straightforward as using the built-in functionality of 'By Dimension' and 'Persistent colors'.
References for Qlik Sense Business Analyst:
Color Consistency Across Charts: The 'By Dimension' and 'Persistent colors' settings are recommended in Qlik Sense documentation when creating multi-chart layouts with shared dimensions, ensuring visual coherence across different charts.
The Persistent colors and By Dimension settings offer a straightforward and maintainable way to create color associations across charts, making option C the verified solution.
質問 # 28
Two customers in an organization want to use an app that contains a finance data set. With different analysis objectives, each customer will only use a subset of that data. Which procedure should the business analyst follow?
- A. Apply Section Access to manage the data for each customer
- B. Unpivot, then re-associate the data tables for each customer
- C. Create multiple visualizations using set analysis
- D. Duplicate and rename the apps for each customer
正解：C
解説：
In Qlik Sense, Set Analysis is one of the most powerful tools available to a Business Analyst for managing different subsets of data within the same app. Since both customers are working with the same finance dataset but have different objectives, creating multiple visualizations using set analysis allows the analyst to tailor the data views for each customer without duplicating the app or creating complex data models.
Key Concepts:
Set Analysis: This feature enables the creation of expressions that define subsets of data, allowing you to filter data within specific visualizations. This is ideal when multiple users need different insights from the same underlying dataset.
Flexibility: Using set analysis, you can specify conditions within individual visualizations so that each user can focus on their own segment of the data without impacting others.
Efficiency: This method avoids redundancy by ensuring you only need one app and one data model, instead of duplicating and maintaining multiple apps or applying complex logic such as Section Access.
Why the Other Options Are Less Suitable:
A . Apply Section Access: While Section Access is useful for managing security and limiting what users can see in the entire dataset, it is primarily designed to restrict data access based on user roles. In this case, both users need access to the same dataset but will conduct different analyses. Section Access would be an overly restrictive and complex solution for this scenario.
C . Duplicate and rename the apps: This is inefficient because it leads to redundancy and makes maintenance harder (e.g., any changes to the dataset or visualizations would need to be applied to both apps). It also increases the risk of inconsistencies across versions of the app.
D . Unpivot and re-associate the data tables: This option is not relevant to the problem, as unpivoting is more appropriate for transforming datasets rather than tailoring views for different users within the same app. It does not address the need for customer-specific analysis objectives.
References for Qlik Sense Business Analyst:
Set Analysis: In the Qlik Sense Business Analyst's toolkit, Set Analysis is covered as a method to manage diverse data subsets within single apps, providing the flexibility needed in multi-user environments without duplicating content.
Efficient Application Design: Best practices suggest maintaining a single app where possible to ensure consistency and ease of maintenance, which aligns with the approach of using Set Analysis.
By using Set Analysis, you provide both customers with tailored data views that are easily managed and updated within a single app. This is why option B is the most effective and verified solution.
質問 # 29
A customer needs to distribute sales data to a variety of teams. The internal analyst team requires a global view of dat a. The sales team requires mobile device access.
Which solution will meet the needs of both teams?
- A. One app with a specific extension for mobile users
- B. One app with various objects
- C. A mashup with various objects
- D. Two apps: one designed for mobile and one for internal use
正解：D
解説：
To meet the needs of both the internal analyst team and the sales team, the best solution is to create two 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, B is 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.
質問 # 30
A business analyst using a shared folder mapped to S:\488957004\ receives an Excel file with more than 100 columns. Many of the columns are duplicates. Any current columns that should be used have the suffix '_c' appended to the column name.
Which action should the business analyst take to load the Excel data?
- A. Deselect the fields that do not have the '_c' suffix in the Data manager table preview
- B. Utilize filter functionality in the Data manager to select only columns with the suffix '_c' with a filter condition
- C. Load all columns because the recommended associations will use only columns with the suffix '_c'
- D. Open the Excel file, remove all columns that do not have the suffix '_c', and save the file to be loaded
正解：A
解説：
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 the Data Manager. The Data Manager provides a preview of the table being loaded, allowing the business analyst to deselect columns that 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, D is the best solution because it allows for selective loading of relevant columns, making it the correct answer.
質問 # 31
A customer needs to demonstrate the value of sales for each month of the year with a rolling 3-month summary. Which visualization should the business analyst recommend to meet the customer's needs?
- A. Mekko chart
- B. Scatter plot
- C. Combo chart
- D. Pie chart
正解：C
解説：
A combo chart is the most suitable visualization to show the value of sales for each month along with a rolling 3-month summary. The combo chart allows you to combine different types of visualizations, such as bars for monthly sales values and a line for the rolling 3-month summary. This provides a clear comparison and tracking of sales trends over time.
Key Concepts:
Rolling Summary: In this case, a 3-month rolling summary can be shown as a line measure in the combo chart, while the sales values for each month can be shown as bars.
Combo Chart: This visualization is ideal for comparing multiple measures on the same axis, such as individual sales values and aggregated rolling summaries.
Why the Other Options Are Less Suitable:
A . Scatter plot: A scatter plot is used to display the relationship between two variables, not to show time-based trends or rolling summaries.
B . Mekko chart: Mekko charts are used for categorical data and comparisons across categories, not for time-based analysis.
D . Pie chart: Pie charts are best suited for showing parts of a whole and are not appropriate for visualizing time-based data or rolling summaries.
References for Qlik Sense Business Analyst:
Combo Charts for Time Series Data: Combo charts are highly recommended when there is a need to compare different types of measures (like individual sales vs. rolling averages) over time in Qlik Sense.
Thus, a combo chart provides the most effective solution for showing both monthly sales values and the rolling 3-month summary, making C the correct answer.
質問 # 32
A business analyst created a visualization that has a color indicator when an order is below a certain fixed profit threshold. This visualization now needs to change so that the threshold can be defined by the user. The user base is approximately 1000 heavy Excel users. These thresholds will be defined by each user somewhat frequently, although the data changes only once per day.
Which action should the business analyst take to update this visualization?
- A. Allow users to define their threshold in a shared spreadsheet and increase the app reload frequency to every hour
- B. Add a threshold field and provide a filter pane for that field for users to select
- C. Introduce a variable for the threshold that is controlled by a variable slider
- D. Create threshold values in the data manager using the Bucket function
正解：C
解説：
The best approach to allow users to frequently adjust the profit threshold in the visualization is to use a variable controlled by a variable slider. This method allows each user to adjust the threshold value independently without requiring any changes to the data model or the visualization itself. Given that the user base consists of heavy Excel users, using a slider provides a familiar and intuitive way to interact with the threshold.
Key Concepts:
Variables and Sliders: Variables can be used to store threshold values, and sliders provide an easy way for users to adjust those variables interactively.
User Interaction: A variable slider is a user-friendly option for adjusting thresholds frequently, especially for users who are accustomed to working with data interactively.
Why the Other Options Are Less Suitable:
A . Threshold field with a filter pane: This option is less flexible and doesn't allow the same dynamic interaction as a variable and slider.
B . Shared spreadsheet and frequent app reloads: This approach is inefficient and would increase the load on the system unnecessarily. It is also less user-friendly for frequent threshold adjustments.
D . Bucket function: The Bucket function is not appropriate for this case, as it creates static groupings, which would not allow the user to adjust the threshold dynamically.
References for Qlik Sense Business Analyst:
Interactive Thresholds with Variables: Qlik Sense's variables and slider objects provide the best mechanism for dynamically controlling thresholds in a visualization.
Thus, introducing a variable for the threshold and controlling it with a variable slider is the best solution, making C the correct answer.
質問 # 33
Refer to the exhibit.
The users of a Qlik Sense app report slow performance. The app contains approximately 10 million rows of dat a. The business analyst notices the following KPI master measure definition:
Left{ Trim( TransactionName), 1 ) * Right ( TransactionName, 5) Which steps should the business analyst complete to improve app performance?
- A. * 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. - B. Change the master measure definition as follows:
subfield( TransactionName, '',!)* subfieldl TransactionName, ' ', 3) - C. Ask the developer of the underlying database to change the structure of the field TransactionName.
- D. In the Data manager, use the Replace function to remove the middle part of the field TransactionName
正解：A
解説：
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 why Option B is 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 the Split function in 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 the subfield() function to 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 the Data 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.
The Replace function would 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:
The Data Manager provides powerful tools for transforming and optimizing data before it is used in visualizations. Pre-processing the data using functions like Split significantly 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 fields allow analysts to create new expressions based on transformed data, ensuring that the app remains efficient while meeting analytical needs.
Thus, the correct solution is to use the Split function to separate the field values and then use a calculated field to multiply the required components, which enhances app performance.
質問 # 34
The human resources department needs to see a distribution of salaries broken down by department with standard deviation indicators.
Which visualization should the developer use?
- A. Scatter plot
- B. Histogram
- C. Distribution plot
- D. Box plot
正解：D
解説：
A box plot is the best visualization for displaying the distribution of salaries broken down by department with standard deviation indicators. Box plots show the spread of data, including key measures like quartiles, median, and outliers, which are useful for analyzing salary distributions. They also naturally incorporate standard deviation indicators through the spread of data.
Key Concepts:
Box Plot: This type of chart is designed for analyzing the distribution of data across different categories (in this case, departments). It shows the spread and variability of data, which can include standard deviations.
Why the Other Options Are Less Suitable:
A . Distribution plot: While a distribution plot can show spread, it's not as effective for showing standard deviation and is less suited for categorical breakdowns.
C . Histogram: A histogram shows the distribution of a single variable, but it doesn't provide the same detailed breakdown as a box plot.
D . Scatter plot: Scatter plots are used for showing relationships between two variables and are not suitable for showing standard deviation across departments.
References for Qlik Sense Business Analyst:
Box Plot for Distribution Analysis: Box plots are ideal for visualizing data distribution and variability across categories, making them the preferred choice for analyzing salary distribution by department.
Thus, the box plot is the best choice for visualizing salary distribution with standard deviation indicators, making B the verified answer.
質問 # 35
A business analyst is building an app to analyze virus outbreaks. They create a bar chart using a dimension of Continent, and a measure of Sum (Knowning sections). They require a secondary bar on the chart, so they create a second measure using Count (MajorCities).
The bar chart adjusts, but no bars are visible for this second measure. Which action should the business analyst take to resolve this issue?
- A. Enable Value labels within the Presentation section of the Appearance properties
- B. Recreate the second measure as an alternative measure
- C. Convert the bar chart to a combo chart and reconfigure the second measure to be a bar
- D. Change the Y-axis Range scale from Auto to Custom and select a suitable Max value
正解：C
解説：
In this scenario, the second measure (Count of MajorCities) is likely not being displayed because the two measures-Sum(Knowing sections) and Count(MajorCities)-are on vastly different scales. When two measures have significantly different ranges, one of them may not be visible on the same Y-axis, causing the issue you're seeing where no bars are visible for the second measure.
By converting the bar chart to a combo chart, the business analyst can display both measures with appropriate configurations. The combo chart allows you to display different measures in different ways, such as using one axis for the first measure (e.g., bars for Sum(Knowing sections)) and another axis for the second measure (e.g., bars for Count(MajorCities)), ensuring that both are visible on the chart.
Key Concepts:
Combo Chart: This type of chart allows you to display multiple measures using different axis scales or types of visualization (e.g., bars and lines).
Scale Mismatch: When two measures differ significantly in scale, they may not be displayed properly on the same axis. A combo chart helps by allowing separate Y-axes for each measure.
Why the Other Options Are Less Suitable:
A . Enable Value labels: While value labels can help show specific data points, they won't resolve the issue of one measure being invisible due to scale differences.
B . Recreate as an alternative measure: This would allow switching between measures, but the requirement is to show both measures simultaneously.
C . Change Y-axis Range to Custom: While adjusting the Y-axis manually might help, it's not the best solution because the scale difference between the two measures might still cause issues, and it would be harder to adjust dynamically.
References for Qlik Sense Business Analyst:
Combo Charts for Multiple Measures: Combo charts are recommended in Qlik Sense when you need to display multiple measures with different scales.
Thus, converting the bar chart to a combo chart ensures both measures are properly displayed, making D the correct answer.
質問 # 36
A business analyst is building an app to analyze virus outbreaks. They create a bar chart using a dimension of Continent, and a measure of Sum (Knowning sections). They require a secondary bar on the chart, so they create a second measure using Count (MajorCities).
The bar chart adjusts, but no bars are visible for this second measure. Which action should the business analyst take to resolve this issue?
- A. Enable Value labels within the Presentation section of the Appearance properties
- B. Recreate the second measure as an alternative measure
- C. Convert the bar chart to a combo chart and reconfigure the second measure to be a bar
- D. Change the Y-axis Range scale from Auto to Custom and select a suitable Max value
正解：C
質問 # 37
A clothing manufacturer has operations throughout Europe and needs to manage access to the data.
There is data for the following countries under the field SACOUNTRY -> France, Spain, United Kingdom and Germany. The application has been designed with Section Access to manage the data displayed.
What is the expected outcome of this Section Access table?
- A. USER1 sees data for France and Spain, USER2 sees data for the UK. ADMIN sees data for France, Spain, Germany and United Kingdom
- B. USER1 does not see data for France and Spain, USER2 does not see data for United Kingdom. ADMIN can not open the application
- C. USER1 does not see data for France and Spain. USER2 does not see data for the United Kingdom. ADMIN sees data for all countries.
- D. USER1 sees data for France and Spain, USER2 sees data for the UK. ADMIN sees data for France, Spain and United Kingdom
正解：A
解説：
In this Section Access script, the roles and access to data for different users are defined based on the SACOUNTRY field. Here's how the data access will work:
ADMIN: The ADMIN user has access to all data because the * in the SACOUNTRY field allows full access to all countries in the dataset.
USER1: This user has access to Spain and France because the SACOUNTRY field specifies these countries for USER1.
USER2: This user has access to United Kingdom because the SACOUNTRY field specifies only the UK for USER2.
Key Concepts:
Section Access: This feature in Qlik Sense controls which data users can see based on their login credentials. The access rights are controlled through fields like ACCESS, USERID, and SACOUNTRY in this case.
Why the Other Options Are Less Suitable:
B and C: These suggest that users won't see data they have access to, which contradicts the defined Section Access script.
D: This incorrectly assumes that ADMIN cannot see Germany, which is not defined in the script.
References for Qlik Sense Business Analyst:
Section Access Best Practices: In Qlik Sense, Section Access tables define the data that users can see, and the use of * for the ADMIN role ensures access to all data.
Thus, A is the correct answer because it matches the expected data access behavior based on the script, making it the verified answer.
質問 # 38
A business analyst is creating an app using a dataset from ServiceNow. The dataset shows information about support cases, including how many days it has been since the case was opened (age).
The app requirements are:
* The dashboard must display support cases in categories based on the age (New, Aging, and Beyond Service Level Agreement)
* The categories will be used multiple times in the dashboard
* Given the volume of support cases, it is expected that the dataset will grow to be very large Which solution is the most efficient way for the business analyst to create this app?
- A. Create an Excel sheet with all possible age values and the corresponding categories to add to the data model
- B. Create a new field for the categories using the Bucket option in the Data manager
- C. Ask the ServiceNow team to create the field in the source dataset
- D. Write a master dimension with a nested IF statement to group ages together
正解：B
解説：
To efficiently categorize support cases based on age (New, Aging, Beyond SLA) for use in multiple places across the dashboard, the Bucket option in the Data Manager is the most efficient approach. Bucketing allows the business analyst to create new categories based on the values in an existing field (in this case, the age of support cases). Since the dataset is expected to grow, creating the categories directly within Qlik Sense ensures that the process is scalable without the need for external tools or extensive coding.
Key Concepts:
Bucket Function: This allows you to group numeric fields into predefined ranges or categories. The function is highly scalable, making it suitable for large datasets.
Efficiency: Creating a new field using Bucketing ensures that the categorization is done directly in the app, avoiding the need for external data sources or nested IF statements, which could impact performance.
Why the Other Options Are Less Suitable:
A . Ask the ServiceNow team to create the field: This would create a dependency on external teams and could delay the development process.
B . Create an Excel sheet: This adds unnecessary complexity and isn't scalable as the dataset grows.
D . Write a master dimension with a nested IF statement: While this could work, it's less efficient for handling large datasets and could result in slower performance.
References for Qlik Sense Business Analyst:
Bucketing Data: Qlik Sense recommends using the Bucketing feature for creating predefined ranges or categories, especially when dealing with large datasets.
Thus, using the Bucket option to create a new field for categories is the most efficient solution, making C the correct answer.
質問 # 39
The business analyst creates one table by concatenating and joining several source tables. This has resulted in a table of several thousand rows that may have several columns containing between 30% and 70% null values. The business analyst needs to understand the level of null values in each field of this table to determine if this is an issue.
Which capability should the business analyst use?
- A. Select each field in the Data model viewer and use the Density value to determine the level of nulls
- B. Inspect each field in the Data model viewer and use the Subset ratio to determine the level of null values
- C. Enable the Preview Panel in the Data model viewer and inspect the data table visually to determine the level of null values
- D. Look at the tags fields for any indication that $null is associated to this field
正解：A
解説：
The Density value 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 the Density value 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, A is the correct answer because the density value provides the required insight into the level of nulls in each field.
質問 # 40
A business analyst is developing an app that requires a complex visualization. The visualization is very similar in style and configuration to another visualization in a different app, but the data models are completely different.
Which action should the business analyst take to most efficiently create the new visualization?
- A. Note the properties of the base visualization and create the new visualization from scratch.
- B. Copy and paste the visualization between the apps, and update the data properties in the new app.
- C. Add the base visualization to the master items and use it as a template for the new visualization.
- D. Open both apps at the same time. Drag the base visualization between apps, then update the data properties.
正解：B
解説：
When working with Qlik Sense apps, a business analyst often encounters situations where visualizations may be highly similar between different apps, even if the underlying data models differ. In such cases, efficiency is crucial, and Qlik Sense provides several methods to reuse visualizations across apps. Let's break down the options:
A . Add the base visualization to the master items and use it as a template for the new visualization.
This option suggests adding the base visualization to the master items. While master items are useful for reusing dimensions, measures, and visualizations within the same app, they do not easily transfer across apps. In this case, since the visualization is required in a different app, this approach would not be the most efficient or feasible.
B . Note the properties of the base visualization and create the new visualization from scratch.
This option involves manually noting the properties and then replicating them in the new app. While this would work, it is labor-intensive and increases the likelihood of human error, especially in complex visualizations. It is not an efficient solution for business analysts looking to save time.
C . Copy and paste the visualization between the apps, and update the data properties in the new app.
This is the most efficient solution. Qlik Sense allows for the copying and pasting of visualizations between different apps, and you can then adjust the properties to fit the new data model. This option enables the business analyst to leverage existing visual work without having to recreate it from scratch. Updating the data properties, such as dimensions and measures, ensures that the visualization functions correctly with the new data model.
D . Open both apps at the same time. Drag the base visualization between apps, then update the data properties.
While this seems like a practical option, Qlik Sense does not allow users to drag and drop visualizations directly between different apps. As a result, this method is not possible.
Key Qlik Sense Business Analyst References:
Copying and pasting visualizations is a common practice in Qlik Sense when working between different apps. The ability to quickly replicate and adapt visualizations across apps helps streamline the development process.
Adjusting data properties such as dimensions and measures ensures that visualizations adapt to different data models without the need for full recreation.
Efficiency and error reduction are critical in app development, and copy-paste functionalities are specifically designed to reduce manual work in such scenarios.
In conclusion, the correct and most efficient action for the business analyst to take is C, copy and paste the visualization, and then update the relevant data properties.
質問 # 41
The VP of Finance is requesting a presentable solution that allows them to share finance information in monthly meetings with C-suite executives. Given the monthly meeting agendas, the solution must be customizable.
Which Qlik Sense feature should be implemented to meet this requirement?
- A. Action Buttons
- B. Bookmarks
- C. Insight Advisor Chat
- D. Storytelling
正解：D
解説：
Storytelling in 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, Storytelling offers the most effective solution for presenting financial data in a customizable format, making A the correct answer.
質問 # 42
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