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2025 100% Free QSBA2024–Useful 100% Free Certification Book Torrent | Qlik Sense Business Analyst Certification Exam - 2024 Exam Sample Questions

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Qlik QSBA2024 Exam Syllabus Topics:

Topic
Details

Topic 1

Prepare and Load Data: This part of the [code] exam assesses the skills of developers and data analysts in preparing and loading data efficiently. It involves the creation and improvement of data models using Data Manager and verifying them through the data model viewer.

Topic 2

Identify Requirements: This section of the exam evaluates the expertise of professionals like solution architects. It emphasizes identifying Qlik Sense's capabilities to address various business needs. Participants will be tested on their ability to propose Key Performance Indicators (KPIs), dimensions, and measures that align with business objectives.

Topic 3

Design Applications: In this portion of the exam, professionals such as business intelligence developers and Qlik Sense designers will be tested on their competency in creating application layouts tailored to specific business demands. Candidates are also expected to showcase how they adapt and improve application designs based on input from stakeholders and evolving business needs.

Topic 4

Develop Application: The final section of the exam measures the ability of developers to build and fine-tune Qlik Sense applications. It covers the entire development process, from initial design to the refinement of applications in real-world scenarios.

Qlik Sense Business Analyst Certification Exam - 2024 Sample Questions (Q39-Q44):

NEW QUESTION # 39
A business analyst needs to rapidly prototype an application design for a prospective customer. The only dataset provided by the customer contains 30 fields, but has over one billion rows. It will take too long to keep loading in its entirety while the analyst develops the data model.
Which action should the business analyst complete in the Data manager?

A. Truncate text fields longer than 256 characters to create preview fields
B. Split the dataset and create a normalized star schema of associated tables
C. Use the Filter data option to reduce the number of rows
D. Deselect text columns with unique data values to reduce the memory footprint

Answer: C

Explanation:
When working with large datasets, such as the one containing over a billion rows in this scenario, loading the entire dataset can be time-consuming, especially during the development phase. Qlik Sense provides a Filter data option in the Data Manager, which allows business analysts to work with a subset of the data during development. This is particularly useful for rapidly prototyping the application design.
Key Concepts:
Filter Data Option: This feature in Qlik Sense allows the analyst to load a smaller sample of the dataset for analysis and development purposes. By filtering out unnecessary rows, the business analyst can quickly build and prototype the application without waiting for the full dataset to load. Once the design is finalized, the full dataset can be reloaded.
Prototyping with Reduced Data: It's often more efficient to work with a smaller dataset during the design phase. This allows for faster iterations and design cycles, especially when working with large datasets.
Why the Other Options Are Less Suitable:
A . Split the dataset and create a normalized star schema of associated tables: This would involve complex data modeling that is not necessarily related to the immediate need of reducing the size of the dataset for prototyping. While star schemas can optimize data models, it's not the quickest way to reduce the number of rows for initial testing.
B . Deselect text columns with unique data values to reduce the memory footprint: This may reduce the memory usage but won't necessarily address the issue of reducing the number of rows. Also, the text columns might be important for the analysis and should not be removed without careful consideration.
D . Truncate text fields longer than 256 characters to create preview fields: Truncating text fields will not significantly reduce the dataset size or the load time. It may also result in losing critical information, which is not ideal for prototyping.
References for Qlik Sense Business Analyst:
Rapid Prototyping: Qlik Sense encourages rapid development of applications by allowing business analysts to work with subsets of the data. The Filter Data option is an important tool for managing large datasets efficiently.
Data Manager Tools: The Data Manager in Qlik Sense provides several tools for reducing the dataset size, and filtering is one of the key options for improving performance during development.
Using the Filter data option allows the business analyst to focus on a smaller subset of data, enabling quicker prototyping and iteration, which makes option C the most effective solution.

NEW QUESTION # 40
A company has sales data where every Customer ID can be assigned to one or more Sales Account ID. Sales Accounts are assigned to one of eight Groups. The business analyst is creating an app with the following requirements:
* Each Group should have a separate sheet
* The Sales Account can only see its own customers
* The Sales Account can navigate only to the sheet for the Group assigned The business analyst has created a Section Access table, in which each Sales Account ID is assigned their CustomerlDs. Which action should the business analyst take next?

A. Use the OSUser() function within the show/hide condition of the sheets to set the required visibility
B. Use the Sales Account ID as a filter on the show/hide condition on the relevant sheet
C. Use the Group as a filter on the show/hide condition on the relevant sheet
D. Use the Group field within the Section Access table, then apply it to the show/hide condition of the sheets

Answer: D

Explanation:
The most effective way to control sheet access based on group assignment is to use the Group field in the Section Access table and apply it to the show/hide condition of the sheets. Each Sales Account ID is already mapped to a Group, so the business analyst can use this Group field to dynamically control which sheets are visible based on the user's Group assignment. This ensures that each Sales Account only sees their respective Group's sheet.
Key Concepts:
Section Access with Groups: By incorporating the Group field into Section Access, the analyst can restrict sheet visibility based on group membership.
Show/Hide Condition: This feature in Qlik Sense allows certain sheets or objects to be displayed or hidden based on conditions, in this case, the user's group.
Why the Other Options Are Less Suitable:
A . Sales Account ID as a filter: The Sales Account ID is used for data filtering but is not the appropriate condition for controlling sheet visibility.
B . Group as a filter on the sheet: While Group can be used as a condition, it must be managed through Section Access to ensure proper visibility control.
D . OSUser() function: While OSUser() can capture the user's login information, using the Group field in Section Access is more efficient for controlling access to specific sheets based on group assignments.
References for Qlik Sense Business Analyst:
Show/Hide Sheets Based on Section Access: Qlik Sense supports the use of Section Access for controlling access to sheets based on user roles and group assignments.
Thus, C is the most appropriate solution because it uses the Group field within Section Access to control sheet visibility, making it the correct answer.

NEW QUESTION # 41
A business analyst is creating an app that contains a bar chart showing the top-selling product categories. The users must be able to control the number of product categories shown.
Which action should the business analyst take?

A. Use firstsortedvalue() function to extract the required product categories
B. Use a rankQ function in the sales expression
C. Create a variable and variable input object and use variable in the sales expression
D. Create a variable and variable input object and use variable in dimension limit field

Answer: D

Explanation:
When users need control over how many product categories are shown in a bar chart, the most effective solution is to use a variable input object. This allows users to dynamically adjust the number of categories displayed.
A: Create a variable and variable input object and use the variable in the dimension limit field.
This is the correct solution. By creating a variable and using the Variable Input object, the user can dynamically control the number of product categories shown in the bar chart by adjusting the dimension limit. This method provides flexibility and an intuitive interface for the user.
B: Use firstsortedvalue() function to extract the required product categories.
The firstsortedvalue() function is typically used to extract the first occurrence of a value based on sorting criteria, but it's not the best approach for controlling the number of displayed categories dynamically.
C: Create a variable and variable input object and use the variable in the sales expression.
While variables can be used in expressions, this approach is less efficient than using the dimension limit field, which is specifically designed for controlling the number of displayed values.
D: Use a rankQ function in the sales expression.
The rankQ function ranks data, but it's not the most efficient or intuitive method for dynamically controlling the number of product categories displayed in a bar chart. It would require more complex expressions compared to the straightforward use of a variable in the dimension limit field.
Key Qlik Sense Business Analyst References:
The Variable Input object allows users to interact with and adjust variables within the app. This is ideal for giving users control over visual elements like the number of categories displayed in a chart.
The Dimension Limit field is specifically designed to control how many items (like product categories) are shown in a chart based on a ranking or expression.
Thus, the best approach to allow users to control the number of product categories displayed is to create a variable and variable input object, and use the variable in the dimension limit field.

NEW QUESTION # 42
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. Scatter plot
B. Combo chart
C. Pivot table
D. Multi KPI

Answer: A

Explanation:
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.

NEW QUESTION # 43
Refer to the exhibit.

An app that will track experiments for rodents (e.g., rats and mice) that navigate mazes (labyrinths) is being developed. Individual rodents are catalogued in the Rodent table, while the Mazes table has metadata for the mazes. The MazeEscapes table holds a record of each attempt at a maze by a rodent. A business analyst needs to build a KPI that will allow users to see how many rodents have made at least one attempt at any maze.
How should the analyst construct the KPI?

A. * Create RodentlD AS RodentlD Counter in the Rodent table.
* Use Count (Distinct RodentID Counter) as the KPI expression.
B. * Create RodentlD AS RodentID_Counter in the MazeEscapes table.
* Use Count (Distinct RodentlD Counter) as the KPI expression.
C. * Create 1 AS RodentID_Counter in the Rodent table.
* Use Sum (RodentlD Counter) as the KPI expression.
D. Create 1 AS RodentID_Counter in the MazeEscapes table.
Use Sum (RodentlD Counter) as the KPI expression.

Answer: B

Explanation:
In this case, we need to count how many unique rodents have made at least one attempt at any maze. Since the relationship between the Rodent table and the MazeEscapes table is a one-to-many relationship (each rodent may attempt several mazes), the best approach is to base the calculation on the MazeEscapes table, as it holds the actual records of rodent attempts.
By creating a new field RodentID_Counter in the MazeEscapes table, the analyst ensures that each rodent's attempt is captured. Using the Count (Distinct RodentID_Counter) as the KPI expression then accurately counts each unique rodent that has made at least one attempt, without counting multiple attempts by the same rodent.
Key Concepts:
Distinct Count: The distinct count ensures that rodents who have made multiple maze attempts are only counted once.
MazeEscapes Table: This table holds the records of each attempt, making it the correct source for this KPI.
Why the Other Options Are Less Suitable:
B . Sum (RodentID_Counter) in the Rodent table: This would incorrectly sum the number of rodents rather than counting unique attempts, leading to inaccurate results.
C . Sum (RodentID_Counter) in the MazeEscapes table: Summing the counter would not account for the distinct rodents, leading to incorrect counting.
D . RodentID_Counter in the Rodent table: This would not correctly reflect the rodents that have made an attempt, as not every rodent in the Rodent table may have attempted a maze.
References for Qlik Sense Business Analyst:
Distinct Count in KPI: It is best practice to use Count(Distinct ...) when working with KPIs that require unique counts, such as counting distinct rodents in this scenario.
Thus, A is the verified answer because it ensures that each rodent is counted once, based on their attempts in the MazeEscapes table.

NEW QUESTION # 44
......

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