Qlik QSBA2024 Qlik Sense Business Analyst Certification Exam - 2024 Exam Practice Test

Answer : D

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.

Answer : C

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.

Answer : A

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.

Answer : C

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.

Answer : A

For the KPI object that meets the requirements of comparing Current Year (CY) sales against Last Year (LY) sales, while ensuring the KPI remains static regardless of selections, we need to leverage Set Analysis with the 1 identifier. This ensures the KPI ignores any selections made by the user.

Option A uses the correct structure of Set Analysis that compares CY sales to LY sales within the APAC region, and the 1 set identifier ensures the KPI does not change based on selections. The logic is structured as follows:

Sum({1 <region={'apac'}, year={$(=max(year))}>} Sales) computes the sales for the APAC region for the current year (CY).

Sum({1 <region={'apac'}, year={$(=max(year)-1)}>} Sales) computes the sales for the APAC region for the previous year (LY).

This expression will ensure that the comparison of sales between CY and LY is made, without being affected by user selections.

Key Concepts:

Set Analysis with 1: The 1 set identifier ensures that selections made by users do not affect the result, making the KPI static.

Comparison of CY vs. LY: The use of $(=max(year)) and $(=max(year)-1) ensures that the current and previous years are dynamically compared.

Why the Other Options Are Less Suitable:

B, C, and D: While these options use a similar structure, they do not correctly handle the measure structure or have syntactical issues. Only Option A properly utilizes the 1 set identifier and dynamic year comparison for the APAC region.

References for Qlik Sense Business Analyst:

Set Analysis for Static KPIs: Using the 1 set identifier in Qlik Sense ensures that a KPI remains static and unaffected by user selections, which is essential for business requirements like this.

Thus, A is the correct choice because it correctly computes the required static KPI for the APAC region, making it the verified answer.

Answer : A

To make the price ranges dynamically adjustable by the application users, a variable input object is the best approach. The business analyst can define a variable that stores the range value, which users can modify directly through a variable input control. This method allows users to change the price ranges interactively, giving them control over the ranges used in the analysis.

Key Concepts:

Variable Input Object: This object allows users to interact with and modify the values of predefined variables directly within a Qlik Sense sheet, which can then be used to adjust calculations dynamically, such as defining custom ranges.

Configurable by Users: This approach gives end-users the flexibility to modify the visualization based on their specific needs without requiring backend changes or reloading the app.

Why the Other Options Are Less Suitable:

B . Create a calculated field in Data manager, using the Class() function: The Class() function is useful for creating static price ranges, but it does not allow for user interaction or dynamic updates to the ranges.

C . Load an independent source file to contain the user-defined boundary values: While this could provide configurable ranges, it's unnecessarily complex and would require more management, and it's not as user-friendly as using a variable.

D . Create the price range dimension using the Buckets feature in Data manager: Similar to the Class() function, this would create static groupings, which wouldn't be dynamically adjustable by the user.

References for Qlik Sense Business Analyst:

Dynamic Controls with Variables: Qlik Sense provides the ability to create variable input objects that allow users to control how visualizations behave dynamically. This feature is highlighted in Qlik Sense's Business Analyst best practices when making interactive applications.

By using a variable and a variable input object, the business analyst enables user interactivity and customization, making A the correct choice.

Answer : C

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.