QSBA2022 Qlik Sense Business Analyst Certification Exam - 2022 Questions and Answers

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.

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.

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.

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.

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.

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 .

To meet the requirement of dynamically changing the number of countries and cities displayed in the visualizations, the business analyst should use variables to control the number of countries and cities shown. By creating two variables (vCountry and vCity), the analyst can use sliders to allow the user to adjust the maximum number of countries (up to 10) and cities (up to 5 per country) that are displayed. These variables can then be applied to each visualization to control the displayed data.

Key Concepts:

Variables : Variables allow users to dynamically adjust values in Qlik Sense visualizations. In this case, sliders can be used to change the number of countries and cities displayed.

Slider Object : Adding a slider enables users to easily adjust the values of the variables vCountry and vCity in a user-friendly manner.

Why the Other Options Are Less Suitable:

B. Input field and dimension limitation : This option is unnecessarily complex and doesn't provide the same dynamic control as using variables and sliders.

C. Input field without sliders : While input fields could work, sliders offer a more intuitive way for users to adjust the values dynamically.

D. Sheet action : Setting a sheet action to limit the data displayed is less flexible and doesn't provide the same dynamic interaction as using variables and sliders.

References for Qlik Sense Business Analyst:

Dynamic Visualizations with Variables : Qlik Sense recommends using variables and interactive objects like sliders to give users control over dynamic data visualizations.

Thus, the most effective solution is to create variables and use sliders to dynamically control the number of countries and cities, making A the correct answer.