Most Recent Qlik QSBA2024 Exam Dumps

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.

To inform a company director when a threshold is breached, Alerting is the most appropriate feature. Qlik Sense allows users to set up automated alerts based on specific conditions or thresholds. These alerts can be configured to notify users when certain criteria are met, making it ideal for keeping the director informed without requiring them to constantly check the application.

Key Concepts:

Alerting: This feature allows users to set conditions (such as when a sales or performance threshold is breached) and automatically send notifications to the relevant individuals.

Automated Notifications: Alerting ensures that the director is notified promptly and automatically when a critical threshold is reached.

Why the Other Options Are Less Suitable:

A . Weekly PDF report: A weekly report would not provide real-time notifications, which are necessary when thresholds are breached.

B . Storytelling: Storytelling is used for presentations, not for monitoring thresholds.

D . Bookmark: A bookmark only saves a particular selection or view, and cannot send notifications when a condition is met.

References for Qlik Sense Business Analyst:

Alerting in Qlik Sense: Qlik Sense's alerting functionality is designed to notify users when specific conditions are triggered, making it ideal for scenarios where timely notifications are critical.

Thus, using Alerting is the best solution to notify the director when a threshold is breached, making C the verified answer.

When users need to filter across many different fields and values in a Qlik Sense dashboard, the most efficient feature they can use is Smart Search. Smart Search allows users to quickly search across all fields within the data model, enabling them to find relevant information and apply filters in a streamlined manner.

A . Smart search This is the correct option. Smart Search enables users to enter search terms and find matches across all fields in the data model, allowing for quick and intuitive filtering. It helps users locate specific data points or filter across multiple fields at once, making it highly efficient when multiple filter panes are needed.

B . Data model viewer The Data Model Viewer provides a visual representation of the relationships between data tables in the model. While it's useful for understanding the data structure, it's not a tool for filtering or user interaction with data.

C . Insight Advisor The Insight Advisor is designed for guided analytics, providing suggestions and generating visualizations based on user queries. It does not offer the comprehensive filtering capabilities that Smart Search does.

D . Governed self-service Governed self-service refers to the balance between providing users with flexibility in creating their own visualizations while maintaining control over data governance. It's not related to filtering or searching data in the same way as Smart Search.

Key Qlik Sense Business Analyst References:

Smart Search in Qlik Sense is designed to provide fast, interactive search capabilities that span across all fields, enabling complex filtering in an easy-to-use interface.

This feature allows users to filter multiple fields simultaneously, saving time and effort when analyzing diverse data sets.

Thus, the correct feature for filtering on multiple values across different fields is Smart Search.

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.

To recreate the dashboard image provided by the HR Director, the following charts are needed:

Map chart: To show the geographical representation of office capacity.

Org chart: To show the company employee structure.

Line chart: To show company retention over time.

Bar chart: To show average employee salary by region.

Key Concepts:

Map Chart: Used to visualize geographical data, such as office capacity across different locations.

Org Chart: Ideal for displaying hierarchical structures, such as the employee structure of a company.

Line Chart: Best suited for showing trends over time, such as employee retention.

Bar Chart: A good choice for comparing salaries across regions.

Why the Other Options Are Less Suitable:

A . Sankey chart: This chart is used for flow or process analysis, not employee structure.

B . Network chart: Network charts show relationships but are not ideal for hierarchical structures like an org chart.

C . Grid chart and KPI chart: These charts are not well-suited for the types of data required in this scenario.

References for Qlik Sense Business Analyst:

Chart Selection for HR Dashboards: Qlik Sense provides various visualization options, and selecting the correct chart for each type of data is essential for accurate and clear representation.

Thus, the correct combination of charts is D---Map chart, org chart, line chart, and bar chart---making it the verified answer.