[2025年03月21日] トップクラスのQSBA2024練習試験問題
実際問題を使ってQSBA2024無料問題集サンプル問題と練習テストエンジン
Qlik QSBA2024 認定試験の出題範囲：
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質問 # 30
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. Total distinct values and Subset ratio for the StudentID field in the Attempts table
- B. Subset ratio and Present distinct values for the ExamID field in the Attempts table
- C. Non-null values and Subset ratio for the StudentID field in the Students table
- D. Present distinct values and Density% for the ExamID field in the Exams table
正解：A
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 # 31
A business analyst is working with a customer to refine the end user experience. The customer has the following requirements:
* Ability to provide these charts to a specific user group
* Minimize the number of navigation clicks between charts
* Achieve fastest screen response time when switching between charts
* Maximize the chart size in terms of screen real estate
Which action should the business analyst take to meet the requirements?
- A. Use a container object to host the required visualizations
- B. Create a single sheet with every required chart on this single sheet
- C. Use Conditional show on all charts and overlay the charts in the same location
- D. Create several sheets (one sheet per client) and use buttons to navigate between sheets
正解：A
解説：
The best solution for minimizing navigation clicks, maximizing screen real estate, and ensuring fast response times is to use a container 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 a container object to host the required visualizations is the best solution, making C the verified answer.
質問 # 32
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. Bookmarks
- B. Insight Advisor Chat
- C. Storytelling
- D. Action Buttons
正解：C
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 # 33
A business analyst is creating an app for the team. A set of selections must be applied every time an app is opened. Which action should the business analyst take to meet this requirement?
- A. Create a mashup and use the API to apply default selections
- B. Use Section Access to predefine the default selections
- C. Create bookmark and set it as default bookmark
- D. Use a sheet action and apply a bookmark named 'Default
正解：C
解説：
In Qlik Sense, default bookmarks allow a set of selections to be applied automatically whenever the app is opened. By creating a bookmark and setting it as the default, the business analyst ensures that the required selections are applied every time the app is opened, which meets the requirement of consistently applying the same selections for all users.
Key Concepts:
Default Bookmark: A default bookmark automatically applies the saved selections when an app is opened, ensuring consistency without manual input from users.
Bookmarking: This feature allows users to save specific selections or states of a dashboard for later use.
Why the Other Options Are Less Suitable:
A . Section Access: Section Access controls data access and security, not default selections.
B . Mashup with API: While this could technically work, it's unnecessarily complex and requires custom coding.
C . Sheet Action: A sheet action could apply a bookmark but would not ensure that the selections are applied at the time of app opening.
References for Qlik Sense Business Analyst:
Default Bookmark for Predefined Selections: This feature is commonly used to ensure that specific selections are always applied when an app is opened.
Thus, D is the best solution for applying default selections, making it the correct answer.
質問 # 34
A business analyst receives an image of a dashboard from the HR Director and is asked to recreate the image in Qlik Sense. The image shows charts for:
* Company employee structure
* Average employee salary by region
* Geographical representation of office capacity
* Company retention over time
Which charts will meet these analysis requirements?
- A. Line chart, sankey chart, map chart, bar chart
- B. Map chart, org chart, line chart, bar chart
- C. Line chart, network chart, bar chart, map chart
- D. Map chart, grid chart, line chart, KPI chart
正解：B
解説：
To recreate the dashboard image provided by the HR Director, the following charts are needed:
Map chart: To show the geographical representation of office capacity.
Org chart: To show the company employee structure.
Line chart: To show company retention over time.
Bar chart: To show average employee salary by region.
Key Concepts:
Map Chart: Used to visualize geographical data, such as office capacity across different locations.
Org Chart: Ideal for displaying hierarchical structures, such as the employee structure of a company.
Line Chart: Best suited for showing trends over time, such as employee retention.
Bar Chart: A good choice for comparing salaries across regions.
Why the Other Options Are Less Suitable:
A . Sankey chart: This chart is used for flow or process analysis, not employee structure.
B . Network chart: Network charts show relationships but are not ideal for hierarchical structures like an org chart.
C . Grid chart and KPI chart: These charts are not well-suited for the types of data required in this scenario.
References for Qlik Sense Business Analyst:
Chart Selection for HR Dashboards: Qlik Sense provides various visualization options, and selecting the correct chart for each type of data is essential for accurate and clear representation.
Thus, the correct combination of charts is D-Map chart, org chart, line chart, and bar chart-making it the verified answer.
質問 # 35
A business analyst receives multiple requests for a variety of different filter panes to be placed on a dashboard. Users need to filter on many different values across different fields.
Which Qlik Sense feature do the users need to learn about to meet their needs?
- A. Smart search
- B. Data model viewer
- C. Governed self-service
- D. Insight Advisor
正解：A
解説：
When users need to filter across many different fields and values in a Qlik Sense dashboard, the most efficient feature they can use is Smart Search. Smart Search allows users to quickly search across all fields within the data model, enabling them to find relevant information and apply filters in a streamlined manner.
A . Smart search
This is the correct option. Smart Search enables users to enter search terms and find matches across all fields in the data model, allowing for quick and intuitive filtering. It helps users locate specific data points or filter across multiple fields at once, making it highly efficient when multiple filter panes are needed.
B . Data model viewer
The Data Model Viewer provides a visual representation of the relationships between data tables in the model. While it's useful for understanding the data structure, it's not a tool for filtering or user interaction with data.
C . Insight Advisor
The Insight Advisor is designed for guided analytics, providing suggestions and generating visualizations based on user queries. It does not offer the comprehensive filtering capabilities that Smart Search does.
D . Governed self-service
Governed self-service refers to the balance between providing users with flexibility in creating their own visualizations while maintaining control over data governance. It's not related to filtering or searching data in the same way as Smart Search.
Key Qlik Sense Business Analyst References:
Smart Search in Qlik Sense is designed to provide fast, interactive search capabilities that span across all fields, enabling complex filtering in an easy-to-use interface.
This feature allows users to filter multiple fields simultaneously, saving time and effort when analyzing diverse data sets.
Thus, the correct feature for filtering on multiple values across different fields is Smart Search.
質問 # 36
A customer is developing over 100 apps, each with several sheets that contain multiple visualizations and text objects. The customer wants to standardize all colors used every object across every app. The customer also needs to be able to change these colors quickly, as required.
Which steps should the business analyst take to make sure the color palette is easily maintained in every app?
- A. * Develop the first app with every variation of object and visualization that will be required
* Duplicate this app to create every other app
* Remove the variations that are not required and adjust the ones needed - B. * Create all color expressions as variables in a text file
* Load it in each app with an include statement
* Use these variables in the color property of all objects - C. * Design all base objects as master visualizations
* Link each object in each app to the relevant master visualization
* Adjust the data properties as required - D. * Store color definitions within a .qvd file
* Have each app load this file as a data island in the model
* Have every object select its required color property from the rows within the data island
正解：B
解説：
In scenarios where a customer needs to standardize colors across multiple apps and be able to update them quickly, using variables in combination with an include statement is the most flexible and maintainable approach.
A . Design all base objects as master visualizations and link each object in each app to the relevant master visualization.
While master visualizations help with consistency within a single app, they don't offer an easy way to update all apps globally. You would need to manually update the colors in every master visualization in each app, which is not efficient for large-scale management.
B . Develop the first app with every variation of object and visualization and duplicate this app.
Duplicating apps will create maintenance challenges. Each app would need to be updated individually if colors or other settings change, which is not scalable for over 100 apps.
C . Create all color expressions as variables in a text file, load it in each app with an include statement, and use these variables in the color property of all objects.
This is the most efficient solution. By storing color definitions in a text file and loading them with an include statement, the business analyst can update the colors in one place, and these updates will be reflected across all apps that use the file. This method ensures easy maintenance and flexibility.
D . Store color definitions within a .qvd file and load it as a data island.
While using a .qvd file is possible, it's not as straightforward as using variables and an include statement. Data islands are typically used for selection purposes, and this method would introduce unnecessary complexity in managing colors.
Key Qlik Sense Business Analyst References:
Variables are widely used in Qlik Sense for managing repeated expressions or values like colors. They can be defined once and reused throughout the app.
Include statements allow external files (like text files containing variables) to be loaded into apps, ensuring that updates made to the text file are automatically reflected in all apps that use it. This creates a flexible and scalable solution for managing standardization across multiple apps.
Thus, the best way to maintain a standardized color palette across all apps is to create all color expressions as variables in a text file and load them into each app using an include statement.
質問 # 37
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. Create a calculated master dimension expression
- C. Use the Replace option in Data manager
- D. Load a lookup table to convert values
正解：D
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 # 38
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 does not see data for France and Spain, USER2 does not see data for United Kingdom. ADMIN can not open the application
- B. USER1 sees data for France and Spain, USER2 sees data for the UK. ADMIN sees data for France, Spain and United Kingdom
- 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, Germany and United Kingdom
正解：D
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 # 39
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. Introduce a variable for the threshold that is controlled by a variable slider
- C. Add a threshold field and provide a filter pane for that field for users to select
- D. Create threshold values in the data manager using the Bucket function
正解：B
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 # 40
A company has recently implemented Qlik Sense. A user is looking to use natural language questions to help create content. Which feature can achieve this goal?
- A. Story and Bookmarks
- B. Associative Engine
- C. Advanced Authoring
- D. Insights Advisor Chat
正解：D
解説：
In Qlik Sense, the Insights Advisor Chat is the feature that allows users to interact with the app through natural 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 Authoring
Advanced 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 Bookmarks
Storytelling 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 Chat
Insights Advisor Chat is 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 Engine
The 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 Chat is 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 is Insights Advisor Chat.
質問 # 41
A business analyst needs to build a chart that enables users to analyze the correlation between the following measures for all products:
* Product Sales ($)
* Order Volume
* Margin%
Which visualization should the business analyst use?
- A. Combo chart
- B. Multi KPI
- C. Scatter plot
- D. Pivot table
正解：C
解説：
A scatter plot is the most appropriate visualization for analyzing the correlation between Product Sales ($), Order Volume, and Margin %. 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, the scatter plot is the most effective visualization for analyzing the correlation between Product Sales, Order Volume, and Margin %, making C the correct answer.
質問 # 42
A marketing team needs to display sales for a limited number of products by providing a bar chart that the user can control. The visualization has several requirements:
* Starts with the top five products
* Allows the user to change the number of products displayed
* Allows the user to scroll through all products on a mini chart
The business analyst creates a bar chat and a variable. Which steps should the business analyst complete next?
- A. * Use the variable to fix the limitation
* Add a slider object and use the variable to set its value - B. * Use the variable to fix the limitation
* Add an input box to enable the user to enter the required value - C. * Add the slider object and use the variable to set its value
* Use the properties to set the number of bars to custom - D. * Add the slider object and use the variable to set its value
* Set the number of bars to custom and use the variable to set its value
正解：D
解説：
To meet the requirement of controlling the number of products displayed in the bar chart, the business analyst should use a slider object tied to a variable. The variable will store the number of products the user wants to display. In the Appearance section of the bar chart's properties, the analyst can set the number of bars to a custom value using the variable, ensuring that the user can dynamically change the number of displayed products.
Key Concepts:
Slider Object: This provides a user-friendly way for users to adjust the number of products displayed in the bar chart.
Custom Bar Limitation: By setting the number of bars displayed to a custom value controlled by the variable, the business analyst ensures that the user can dynamically adjust how many products are shown.
Why the Other Options Are Less Suitable:
B . Use the variable to fix the limitation and add an input box: While this could work, sliders provide a better, more intuitive user experience than input boxes for adjusting values dynamically.
C . Use the variable to fix the limitation and add a slider: This is almost correct, but it misses the step of setting the number of bars to a custom value using the variable.
D . Add the slider object and set its value, but without custom bar settings: While adding a slider is correct, not setting the number of bars to custom using the variable means the user wouldn't be able to dynamically control the number of displayed products.
References for Qlik Sense Business Analyst:
Dynamic Control with Variables and Sliders: Qlik Sense best practices recommend using sliders and variables to give users control over visualizations, particularly when it comes to dynamically limiting data displayed.
Thus, adding the slider object and setting the number of bars to a custom value controlled by the variable is the best solution, making A the verified answer.
質問 # 43
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. Open the Excel file, remove all columns that do not have the suffix '_c', and save the file to be loaded
- C. Utilize filter functionality in the Data manager to select only columns with the suffix '_c' with a filter condition
- D. Load all columns because the recommended associations will use only columns with the suffix '_c'
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 # 44
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. Write a master dimension with a nested IF statement to group ages together
- 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. Create an Excel sheet with all possible age values and the corresponding categories to add to the data model
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 # 45
A business analyst has access to all of a company's data for the past 10 years. The source table consists of the following fields: TransactionID, TransactionTime, Transaction Date, Transaction Year, Cardholder, Cardholder address, Cardissuer, and Amount.
Users request to create an app based on this source with the following requirements:
* Users only review the data for the past 2 years
* Data must be updated daily
* Users should not view cardholder info
Which steps should the business analyst complete to improve the app performance?
- A. * Delete Cardholder and time fields in Data manager
* Use set analysis to show data based on transaction year
* Use an API to perform a daily reload task - B. * Delete Cardholder and time fields in Data manager
* Use a bookmark based on auto-calendar fields
* Use the reload function in the sheet Editor asset panel - C. * Deselect Cardholder and time fields in Data manager
* Apply a filter to extract data based on transaction year
* Request a daily reload task from the system admin - D. * Deselect Cardholder and time fields in Data manager
* Use a filter pane based on auto-calendar fields
* Perform a daily reload via the Data manager
正解：C
解説：
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. By deselecting the Cardholder and time fields in the Data Manager, the analyst ensures that sensitive information is not loaded. Applying a filter to extract data based on transaction year ensures 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, D is the correct solution, making it the verified answer.
質問 # 46
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. Copy and paste the visualization between the apps, and update the data properties in the new app.
- B. Add the base visualization to the master items and use it as a template for the new visualization.
- C. Note the properties of the base visualization and create the new visualization from scratch.
- D. Open both apps at the same time. Drag the base visualization between apps, then update the data properties.
正解：A
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 # 47
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. Pie chart
- B. Combo chart
- C. Mekko chart
- D. Scatter plot
正解：B
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 # 48
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. Convert the bar chart to a combo chart and reconfigure the second measure to be a bar
- C. Recreate the second measure as an alternative measure
- D. Change the Y-axis Range scale from Auto to Custom and select a suitable Max value
正解：B
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 # 49
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