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100% Pass 2025 QSBA2024: Latest Qlik Sense Business Analyst Certification Exam - 2024 Exam Overviews

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Qlik Sense Business Analyst Certification Exam - 2024 Sample Questions (Q26-Q31):

NEW QUESTION # 26
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. Use the Filter data option to reduce the number of rows
B. Deselect text columns with unique data values to reduce the memory footprint
C. Truncate text fields longer than 256 characters to create preview fields
D. Split the dataset and create a normalized star schema of associated tables

Answer: A

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 # 27
A data analyst is working on a new Qlik Sense application and realizes that some of the required data sources have already been used in previous applications. To streamline the data loading process and maintain consistency, the analyst decides to leverage existing data connections.
What actions should the analyst take to utilize the pre-existing data connections in Qlik Sense?

A. Export the data connection from the old application and import it into the new one
B. Use a Qlik Sense extension to search and replicate data connections from other applications
C. Copy the script from the old application and paste it into the new application's script editor
D. Access the Data load editor and select the desired data connection from the list of available connections

Answer: D

Explanation:
In Qlik Sense, data connections are reusable objects that allow multiple apps to connect to the same data sources. To leverage existing connections, the business analyst should go to the Data Load Editor and select the desired connection from the list of available connections. This ensures that the analyst uses the same data sources, promoting consistency across apps.
Key Concepts:
Data Connections: Qlik Sense allows users to create and manage connections to external data sources. These connections can be reused across multiple applications.
Data Load Editor: This is where existing data connections can be accessed and used in new applications, streamlining the data loading process.
Why the Other Options Are Less Suitable:
A . Copy the script from the old application and paste it into the new application's script editor: While this could work, it's not the most efficient method, as it doesn't reuse the existing data connection object, and it's prone to errors.
C . Export the data connection from the old application and import it into the new one: Qlik Sense doesn't require exporting and importing data connections since they are already available globally for reuse across apps.
D . Use a Qlik Sense extension to search and replicate data connections: This is unnecessary because Qlik Sense already allows direct access to existing data connections through the Data Load Editor.
References for Qlik Sense Business Analyst:
Reusing Data Connections: One of the key features of Qlik Sense is its ability to reuse data connections across apps, which helps maintain consistency and reduces the need for redundant setups.
Thus, the correct approach is to access the Data Load Editor and select the pre-existing data connection, making B the verified answer.

NEW QUESTION # 28
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. Present distinct values and Density% for the ExamID field in the Exams table
B. Total distinct values and Subset ratio for the StudentID field in the Attempts table
C. Subset ratio and Present distinct values for the ExamID field in the Attempts table
D. Non-null values and Subset ratio for the StudentID field in the Students table

Answer: B

Explanation:
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.

NEW QUESTION # 29
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

Answer: C

Explanation:
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.

NEW QUESTION # 30
Refer to the exhibit.

Refer to the exhibits.
A business analyst must add a list of temporary employees (interns) to the current sales app. The app contains an existing employees table. When the business analyst profiles the data, the association view displays possible associations as shown.
Which action should the business analyst take in Data manager to meet the requirements?

A. Force an association between the InternEmp and the Orders tables
B. Create an association between the EmpID and EmployeelD fields
C. Concatenate the InternEmp table to the Employees tables within Data manager
D. Create a concatenated key to associate the Employees and InternEmp tables

Answer: B

Explanation:
The InternEmp table contains information about temporary employees (interns), and the Employees table contains regular employee data. To properly link these two tables, the business analyst needs to create an association between the EmpID in the InternEmp table and the EmployeeID in the Employees table. This will ensure that the two tables are correctly associated based on the employee identifiers, allowing the system to relate both tables in the data model.
Key Concepts:
Association: Qlik Sense automatically suggests associations between tables based on field names. By linking EmpID from InternEmp with EmployeeID from Employees, the tables can be properly related in the data model.
Association View: The association view in Data Manager helps visualize how tables are connected and suggests appropriate links between tables based on common fields.
Why the Other Options Are Less Suitable:
A . Create a concatenated key: Concatenation is unnecessary for this scenario since the data model relies on direct associations between keys.
B . Concatenate the tables: Concatenating the InternEmp table into the Employees table would combine the records, but it's not appropriate since the two tables should remain separate entities.
C . Force an association between InternEmp and Orders: There's no need to associate InternEmp with Orders directly since the focus is on employees and interns.
References for Qlik Sense Business Analyst:
Field Associations in Qlik Sense: Properly associating fields between tables is crucial for building a clean and efficient data model in Qlik Sense.
Thus, creating an association between EmpID and EmployeeID is the best approach, making D the correct answer.

NEW QUESTION # 31
......

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