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Exam QSBA2024 Study Solutions | QSBA2024 Latest Exam Guide

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Qlik QSBA2024 Exam Syllabus Topics:

Topic
Details

Topic 1

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 2

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 3

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 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 (Q34-Q39):

NEW QUESTION # 34
The business analyst creates one table by concatenating and joining several source tables. This has resulted in a table of several thousand rows that may have several columns containing between 30% and 70% null values. The business analyst needs to understand the level of null values in each field of this table to determine if this is an issue.
Which capability should the business analyst use?

A. Enable the Preview Panel in the Data model viewer and inspect the data table visually to determine the level of null values
B. Inspect each field in the Data model viewer and use the Subset ratio to determine the level of null values
C. Look at the tags fields for any indication that $null is associated to this field
D. Select each field in the Data model viewer and use the Density value to determine the level of nulls

Answer: D

Explanation:
The Density value in the Data Model Viewer provides a measure of how "dense" or "sparse" a field is in terms of data completeness. A higher density value means fewer nulls, while a lower value indicates more nulls. By checking the density value for each field, the business analyst can determine the percentage of non-null values, which is critical for understanding data quality and completeness.
Key Concepts:
Density Value: This is a measure in Qlik Sense that indicates the proportion of non-null values in a field. A field with a high density is mostly populated, while a lower density indicates a high proportion of null values.
Data Model Viewer: This tool allows analysts to inspect the structure and quality of data fields, including metrics such as density.
Why the Other Options Are Less Suitable:
B . Preview Panel: While the Preview Panel shows sample data, it does not provide a comprehensive measure of null values and is more suited for a quick glance rather than detailed analysis.
C . Tags fields with $null: This would show if the field contains any nulls, but it wouldn't quantify the level of nulls.
D . Subset Ratio: The subset ratio compares values across related tables, not null values within individual fields.
References for Qlik Sense Business Analyst:
Data Quality in Qlik Sense: Using the Density value is the best way to assess the proportion of null values in a field, making it ideal for the business analyst to understand the completeness of the data.
Thus, A is the correct answer because the density value provides the required insight into the level of nulls in each field.

NEW QUESTION # 35
A customer is developing over 100 apps, each with several sheets that contain multiple visualizations and text objects. The customer wants to standardize all colors used every object across every app. The customer also needs to be able to change these colors quickly, as required.
Which steps should the business analyst take to make sure the color palette is easily maintained in every app?

A. * Create all color expressions as variables in a text file
* Load it in each app with an include statement
* Use these variables in the color property of all objects
B. * Store color definitions within a .qvd file
* Have each app load this file as a data island in the model
* Have every object select its required color property from the rows within the data island
C. * Design all base objects as master visualizations
* Link each object in each app to the relevant master visualization
* Adjust the data properties as required
D. * Develop the first app with every variation of object and visualization that will be required
* Duplicate this app to create every other app
* Remove the variations that are not required and adjust the ones needed

Answer: A

Explanation:
In scenarios where a customer needs to standardize colors across multiple apps and be able to update them quickly, using variables in combination with an include statement is the most flexible and maintainable approach.
A . Design all base objects as master visualizations and link each object in each app to the relevant master visualization.
While master visualizations help with consistency within a single app, they don't offer an easy way to update all apps globally. You would need to manually update the colors in every master visualization in each app, which is not efficient for large-scale management.
B . Develop the first app with every variation of object and visualization and duplicate this app.
Duplicating apps will create maintenance challenges. Each app would need to be updated individually if colors or other settings change, which is not scalable for over 100 apps.
C . Create all color expressions as variables in a text file, load it in each app with an include statement, and use these variables in the color property of all objects.
This is the most efficient solution. By storing color definitions in a text file and loading them with an include statement, the business analyst can update the colors in one place, and these updates will be reflected across all apps that use the file. This method ensures easy maintenance and flexibility.
D . Store color definitions within a .qvd file and load it as a data island.
While using a .qvd file is possible, it's not as straightforward as using variables and an include statement. Data islands are typically used for selection purposes, and this method would introduce unnecessary complexity in managing colors.
Key Qlik Sense Business Analyst References:
Variables are widely used in Qlik Sense for managing repeated expressions or values like colors. They can be defined once and reused throughout the app.
Include statements allow external files (like text files containing variables) to be loaded into apps, ensuring that updates made to the text file are automatically reflected in all apps that use it. This creates a flexible and scalable solution for managing standardization across multiple apps.
Thus, the best way to maintain a standardized color palette across all apps is to create all color expressions as variables in a text file and load them into each app using an include statement.

NEW QUESTION # 36
A business analyst has access to all of a company's data for the past 10 years. The source table consists of the following fields: TransactionID, TransactionTime, Transaction Date, Transaction Year, Cardholder, Cardholder address, Cardissuer, and Amount.
Users request to create an app based on this source with the following requirements:
* Users only review the data for the past 2 years
* Data must be updated daily
* Users should not view cardholder info
Which steps should the business analyst complete to improve the app performance?

A. * Deselect Cardholder and time fields in Data manager
* Apply a filter to extract data based on transaction year
* Request a daily reload task from the system admin
B. * Delete Cardholder and time fields in Data manager
* Use set analysis to show data based on transaction year
* Use an API to perform a daily reload task
C. * Deselect Cardholder and time fields in Data manager
* Use a filter pane based on auto-calendar fields
* Perform a daily reload via the Data manager
D. * Delete Cardholder and time fields in Data manager
* Use a bookmark based on auto-calendar fields
* Use the reload function in the sheet Editor asset panel

Answer: A

Explanation:
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.

NEW QUESTION # 37
A business analyst receives multiple requests for a variety of different filter panes to be placed on a dashboard. Users need to filter on many different values across different fields.
Which Qlik Sense feature do the users need to learn about to meet their needs?

A. Data model viewer
B. Smart search
C. Insight Advisor
D. Governed self-service

Answer: B

Explanation:
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.

NEW QUESTION # 38
A clothing manufacturer has operations throughout Europe and needs to manage access to the data.
There is data for the following countries under the field SACOUNTRY -> France, Spain, United Kingdom and Germany. The application has been designed with Section Access to manage the data displayed.

What is the expected outcome of this Section Access table?

A. USER1 does not see data for France and Spain. USER2 does not see data for the United Kingdom. ADMIN sees data for all countries.
B. USER1 sees data for France and Spain, USER2 sees data for the UK. ADMIN sees data for France, Spain, Germany and United Kingdom
C. USER1 sees data for France and Spain, USER2 sees data for the UK. ADMIN sees data for France, Spain and United Kingdom
D. USER1 does not see data for France and Spain, USER2 does not see data for United Kingdom. ADMIN can not open the application

Answer: B

Explanation:
In this Section Access script, the roles and access to data for different users are defined based on the SACOUNTRY field. Here's how the data access will work:
ADMIN: The ADMIN user has access to all data because the * in the SACOUNTRY field allows full access to all countries in the dataset.
USER1: This user has access to Spain and France because the SACOUNTRY field specifies these countries for USER1.
USER2: This user has access to United Kingdom because the SACOUNTRY field specifies only the UK for USER2.
Key Concepts:
Section Access: This feature in Qlik Sense controls which data users can see based on their login credentials. The access rights are controlled through fields like ACCESS, USERID, and SACOUNTRY in this case.
Why the Other Options Are Less Suitable:
B and C: These suggest that users won't see data they have access to, which contradicts the defined Section Access script.
D: This incorrectly assumes that ADMIN cannot see Germany, which is not defined in the script.
References for Qlik Sense Business Analyst:
Section Access Best Practices: In Qlik Sense, Section Access tables define the data that users can see, and the use of * for the ADMIN role ensures access to all data.
Thus, A is the correct answer because it matches the expected data access behavior based on the script, making it the verified answer.

NEW QUESTION # 39
......

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