RELIABLE QSBA2024 MOCK TEST - QLIK AUTHENTIC QSBA2024 EXAM QUESTIONS: QLIK SENSE BUSINESS ANALYST CERTIFICATION EXAM - 2024 PASS CERTIFY

Reliable QSBA2024 Mock Test - Qlik Authentic QSBA2024 Exam Questions: Qlik Sense Business Analyst Certification Exam - 2024 Pass Certify

Reliable QSBA2024 Mock Test - Qlik Authentic QSBA2024 Exam Questions: Qlik Sense Business Analyst Certification Exam - 2024 Pass Certify

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Qlik QSBA2024 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Design Applications: In this portion of the exam, professionals such as business intelligence developers and Qlik Sense designers will be tested on their competency in creating application layouts tailored to specific business demands. Candidates are also expected to showcase how they adapt and improve application designs based on input from stakeholders and evolving business needs.
Topic 2
  • Prepare and Load Data: This part of the [code] exam assesses the skills of developers and data analysts in preparing and loading data efficiently. It involves the creation and improvement of data models using Data Manager and verifying them through the data model viewer.
Topic 3
  • Develop Application: The final section of the exam measures the ability of developers to build and fine-tune Qlik Sense applications. It covers the entire development process, from initial design to the refinement of applications in real-world scenarios.
Topic 4
  • Identify Requirements: This section of the exam evaluates the expertise of professionals like solution architects. It emphasizes identifying Qlik Sense's capabilities to address various business needs. Participants will be tested on their ability to propose Key Performance Indicators (KPIs), dimensions, and measures that align with business objectives.

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Qlik Sense Business Analyst Certification Exam - 2024 Sample Questions (Q15-Q20):

NEW QUESTION # 15
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. Total distinct values and Subset ratio for the StudentID field in the Attempts table
  • B. Present distinct values and Density% for the ExamID field in the Exams table
  • C. Non-null values and Subset ratio for the StudentID field in the Students table
  • D. Subset ratio and Present distinct values for the ExamID field in the Attempts table

Answer: A

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 # 16
Refer to the exhibit.

The users of a Qlik Sense app report slow performance. The app contains approximately 10 million rows of dat a. The business analyst notices the following KPI master measure definition:
Left{ Trim( TransactionName), 1 ) * Right ( TransactionName, 5) Which steps should the business analyst complete to improve app performance?

  • A. In the Data manager, use the Replace function to remove the middle part of the field TransactionName
  • B. Ask the developer of the underlying database to change the structure of the field TransactionName.
  • C. Change the master measure definition as follows:
    subfield( TransactionName, '',!)* subfieldl TransactionName, ' ', 3)
  • D. * 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.

Answer: D

Explanation:
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.


NEW QUESTION # 17
A business analyst created a visualization that has a color indicator when an order is below a certain fixed profit threshold. This visualization now needs to change so that the threshold can be defined by the user. The user base is approximately 1000 heavy Excel users. These thresholds will be defined by each user somewhat frequently, although the data changes only once per day.
Which action should the business analyst take to update this visualization?

  • A. Introduce a variable for the threshold that is controlled by a variable slider
  • B. Create threshold values in the data manager using the Bucket function
  • C. Allow users to define their threshold in a shared spreadsheet and increase the app reload frequency to every hour
  • D. Add a threshold field and provide a filter pane for that field for users to select

Answer: A

Explanation:
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.


NEW QUESTION # 18
A business analyst receives an image of a dashboard from the HR Director and is asked to recreate the image in Qlik Sense. The image shows charts for:
* Company employee structure
* Average employee salary by region
* Geographical representation of office capacity
* Company retention over time
Which charts will meet these analysis requirements?

  • A. Line chart, sankey chart, map chart, bar chart
  • B. Map chart, grid chart, line chart, KPI chart
  • C. Map chart, org chart, line chart, bar chart
  • D. Line chart, network chart, bar chart, map chart

Answer: C

Explanation:
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.


NEW QUESTION # 19
The sales manager is investigating the relationship between Sales and Margin to determine if this relationship is linear when choosing the dimension Customer or Product Category.
The sales manager wants to have the potential percentage Sales for each Stage (Initial to Won) of the sales process.
Which visualizations will meet these requirements?

  • A. Scatter plot: Measures X-axis Sales and Y-axis Margin, Alternative dimensions Customer or Product category Funnel chart: Segments Stage, Width Sales
  • B. Distribution plot: Alternative measures Sales and Margin, Alternatives dimensions Customer or Product category Bar chart: Dimension Stage, Measure Sales
  • C. Scatter plot: Measures X-axis Sales and Y-axis Margin, Dimensions Customer or Product category Bar chart: Dimension Stage, Measure Sales
  • D. Combo chart: Measures Sales and Margin, Dimensions Customer or Product category Pie chart: Dimension Stage, Measure Sales

Answer: A

Explanation:
For analyzing the relationship between Sales and Margin, a scatter plot is ideal, as it allows you to visualize the relationship between two measures (Sales and Margin) across various dimensions such as Customer or Product Category. The funnel chart is perfect for visualizing stages in a sales process, as it shows how sales progress from the initial stage to the final (Won) stage, with the width of each segment representing the total sales for each stage.
Key Concepts:
Scatter Plot: This type of chart is specifically designed to visualize the correlation or relationship between two measures, making it ideal for analyzing Sales versus Margin across different dimensions.
Funnel Chart: This chart is particularly suited for visualizing the sales stages, as it visually demonstrates the proportion of sales moving through each stage of the sales funnel.
Why the Other Options Are Less Suitable:
A . Scatter plot and Bar chart: While a scatter plot is correct for analyzing Sales and Margin, a bar chart won't adequately represent the different stages of the sales process as effectively as a funnel chart.
C . Combo chart and Pie chart: A combo chart could potentially work, but it would not show the relationship between Sales and Margin as clearly as a scatter plot. A pie chart is also less effective for representing stages in a sales funnel.
D . Distribution plot and Bar chart: A distribution plot does not effectively show the relationship between two measures, and a bar chart isn't the best choice for visualizing the stages of a sales process.
References for Qlik Sense Business Analyst:
Scatter Plot for Relationships: This chart type is highly recommended when exploring relationships between two continuous variables, such as Sales and Margin.
Funnel Charts: These are ideal for visualizing how data moves through various stages of a process, such as sales stages, from initial engagement to final sale.
Therefore, the combination of a scatter plot and a funnel chart provides the best solution, making B the correct answer.


NEW QUESTION # 20
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