Qlik QSBA2024 Exam Actual Questions

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.

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 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.

In Qlik Sense, when leadership requests a high-level summary such as the total cost of delivery overall, the most efficient way to present this information is by using a KPI object. The KPI object is specifically designed to display a single, important metric in a simple and clear format.

A . Use the line chart to add up each month-year to get to the number required. This option is not efficient because it requires manual effort to add up the values from the line chart for each period. Additionally, this method is prone to human error and would be time-consuming during a presentation.

B . Create a KPI object that shows the total cost of delivery. The most appropriate action here is to use a KPI object to display the overall total cost of delivery. A KPI in Qlik Sense is specifically designed to display single, aggregate measures in a clean and concise way, making it the perfect choice for presenting high-level summaries to leadership.

C . Adjust the line layer on the map to reflect the cost of delivery. While it is possible to adjust the map, the map is primarily used for spatial analysis. Modifying it to reflect the overall cost of delivery would not be as intuitive or effective as using a KPI object. Additionally, it could lead to unnecessary clutter and confusion for the audience.

D . Select all products in the scatter plot to see the total delivery cost. Selecting all products in the scatter plot would not give the desired result because the scatter plot is designed to show relationships between variables (cost of delivery and time-to-deliver). It's not ideal for displaying aggregate values like total cost.

Key Qlik Sense Business Analyst References:

KPI objects are ideal for presenting single, key metrics such as the total cost of delivery. They provide a straightforward, visually clear representation of high-level performance indicators.

Best practices in dashboard development emphasize the importance of creating specific visualizations that address both granular and high-level data needs. KPI objects fulfill the need for high-level summaries, particularly in leadership presentations.

Thus, the best way to show the total cost of delivery to leadership is to create a KPI object.

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.