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QSBA2024 100% Exam Coverage | QSBA2024 Valid Braindumps

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Qlik QSBA2024 Exam Syllabus Topics:

Topic
Details

Topic 1

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 2

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.

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

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.

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Qlik Sense Business Analyst Certification Exam - 2024 Sample Questions (Q11-Q16):

NEW QUESTION # 11
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. Map chart, org chart, line chart, bar chart
B. Line chart, sankey chart, map chart, bar chart
C. Line chart, network chart, bar chart, map chart
D. Map chart, grid chart, line chart, KPI chart

Answer: A

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 # 12
A business analyst designs a visualization to analyze a count of products by fixed price ranges. The customer now wants the price ranges to be dynamically modified so they are configurable by the application users. The business analyst modified the dimension axis on the visualization.
Which step should the business analyst complete next?

A. Load an independent source file to contain the user-defined boundary values
B. Create the price range dimension using the Buckets feature in Data manager
C. Define a variable and use it in a variable input object on the sheet
D. Create a calculated field in Data manager, using the Class() function

Answer: C

Explanation:
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.

NEW QUESTION # 13
A business analyst needs to rapidly prototype an application design for a prospective customer. The only dataset provided by the customer contains 30 fields, but has over one billion rows. It will take too long to keep loading in its entirety while the analyst develops the data model.
Which action should the business analyst complete in the Data manager?

A. Truncate text fields longer than 256 characters to create preview fields
B. Split the dataset and create a normalized star schema of associated tables
C. Deselect text columns with unique data values to reduce the memory footprint
D. Use the Filter data option to reduce the number of rows

Answer: D

Explanation:
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.

NEW QUESTION # 14
An app needs to load a few hundred rows of data from a .csv text file. The file is the result of a concatenated data dump by multiple divisions across several countries. These divisions use different internal systems and processes, which causes country names to appear differently. For example, the United States of America appears in several places as 'USA', 'U.S.A.', or 'US'.
For the country dimension to work properly in the app, the naming of countries must be standardized in the data model.
Which action should the business analyst complete to address this issue?

A. Create a calculated master dimension expression
B. Load a lookup table to convert values
C. Use the Replace option in Data manager
D. Cleanse the source text file prior to loading

Answer: B

Explanation:
In Qlik Sense, when dealing with inconsistent naming conventions across different systems or divisions (like the variation in country names), the best practice is to standardize the data during the loading process. Using a lookup table is the most efficient approach to achieve this. This involves loading a separate table that contains all variations of a country name along with the standardized version. During the load process, Qlik Sense can then map the varying names to a common value.
Key Concepts:
Lookup Table: A lookup table contains key-value pairs where different versions of a data element (like country names) are mapped to a single standard value. In this case, the lookup table could have entries like USA, U.S.A., US all mapped to United States of America.
Data Standardization: This is crucial in ensuring consistent analysis across datasets. By converting variations of country names into a single consistent value, the business analyst ensures that all data visualizations and analysis will treat "USA", "US", etc., as the same entity.
Why the Other Options Are Less Suitable:
A . Create a calculated master dimension expression: While this could theoretically work by creating a calculated expression to handle variations, it's not scalable or maintainable, especially as new variations in country names could appear in future data loads.
C . Cleanse the source text file prior to loading: This option would require modifying the raw data files manually, which is time-consuming and not sustainable if data is frequently updated or if the number of variations is extensive.
D . Use the Replace option in Data manager: The Replace option in the Data Manager could work on a small scale, but it requires manual intervention each time, which is not efficient or sustainable when new data is loaded. Also, it's more useful for one-off corrections than for handling systemic issues across multiple data loads.
References for Qlik Sense Business Analyst:
Data Modeling Best Practices: Lookup tables are a common approach to resolve issues of inconsistent data across multiple sources. They ensure that data is consistently represented in visualizations and reduce the need for manual intervention.
Data Cleansing During Loading: Qlik Sense allows for transformation and data cleansing during the data load process. A lookup table is part of this capability and ensures that the data loaded into the app is clean and consistent.
Using a lookup table is the most scalable and maintainable approach to standardizing country names in this scenario, which is why option B is the verified solution.

NEW QUESTION # 15
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. Distribution plot: Alternative measures Sales and Margin, Alternatives dimensions Customer or Product category Bar chart: Dimension Stage, Measure Sales
B. Combo chart: Measures Sales and Margin, Dimensions Customer or Product category Pie 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. Scatter plot: Measures X-axis Sales and Y-axis Margin, Alternative dimensions Customer or Product category Funnel chart: Segments Stage, Width Sales

Answer: D

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 # 16
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