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Qlik Sense Business Analyst Certification Practice Test

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Exam Name: Qlik Sense Business Analyst Certification
Exam Format: Multiple-choice, multiple-response, and scenario-based questions
Number of Questions: ~40-60 questions
Duration: ~60-90 minutes (varies by test version)
Passing Score: ~70% (may vary)
Delivery Method: Online proctored or at a Pearson VUE test center

- Based on business requirements, identify Qlik products, needed for the solution (QSE, QDC, QABDI, ODAG, Qlik Core, Attunity, Insight Bot, NPrinting, etc.)
- Explain Qlik Sense features (e.g., smart search, responsive design, accessibility features, themes, etc.) and how they impact app design
- Describe the differences between the Qlik deployment options
- Based on business requirements, identify KPIs, dimensions and measures

- Ask appropriate questions to understand the needs of the potential users of the Qlik Sense application
- Identify user types and their typical devices to use to access apps
- Explain the purpose of APIs, server-side extensions (such as R, Python), Qlik GeoAnalytics, web mashups, widgets, section access
- Explain and interpret results from Qlik Associative Engine
- Identify Qlik Cognitive Engine uses
- Consider performance during data loading and application development (removing unused columns, consider calculation condition)

- Create a basic data model using Data Manager (e.g., spreadsheets, CSV, flat files, QVDs, etc.)
- Define the steps to load and associate data
- Apply filters while loading data in Data Manager
- Manually create data table in Data Manager (creates Inline Load script)
- Explain synthetic keys and possible methods of resolution
- Create folder and file data connections
- Leverage data connections already in Qlik Sense Enterprise

- Based on the business requirements and desired insight, determine the optimal number of charts, correct chart type, order of dimensions, use of color, and measures
- Design the order of the sheets in an application to provide an overall flow matching the expectations of the user journey (DAR concept)
- Select object types appropriate for the required data analysis (e.g., a line chart to show a trend over time)
- Understand when and why to use an alternate chart recommendation
- Identify the proper expression to create the appropriate visualization to meet the business requirements

- Explain the impact of using mobiles devices on app design
- Leverage appropriate method for data comparisons (filters, bookmarks, alternate states, set analysis)
- Distinguish between situations when data security requirements need to use section access or security rules
- Add dimensions, measures, and objects
- Use the latest objects and features in the Visualization Bundle, e.g., trellis chart, Profit & Loss pivot table
- Use Advanced Authoring features, e.g., specify a default landing sheet, native container object, etc.
- Set up visualizations with alternate states

- Change the grid size after adding objects
- Create and use variables
- Use custom color in charts (e.g., ColorMix, CSS colors, If statements, etc.)
- Know what extensions are and when to use them
- Create a story
- Create master items

- Apply filters and create bookmarks
- Use advanced functions like AGGR and set analysis
- Perform tasks around making a production ready application (e.g., create a thumbnail image, appropriate title, etc.)
- Use Insight Advisor to generate visualizations
- Use chart suggestions to change visualization type
- Select appropriate screen layout



- Understanding Qlik Sense’s associative model
- Differences between QlikView and Qlik Sense
- Qlik Sense deployment options (Qlik Sense Desktop, Enterprise, Cloud)
- Qlik Sense Hub and its components (Sheets, Stories, Apps)
- Data model optimization techniques

- Associative Engine – Qlik’s in-memory data indexing technology
- In-memory processing – Data loaded into RAM for fast analysis
- QIX Engine – The underlying engine powering Qlik Sense
- QMC (Qlik Management Console) – Admin tool for managing Qlik Sense Enterprise
- Qlik Sense Hub – Central interface for accessing apps and visualizations

- Loading data from various sources (Excel, CSV, SQL, Web, REST APIs)
- Using the Data Load Editor and Script Editor
- Understanding ETL (Extract, Transform, Load) processes
- Optimizing data models (Star Schema, Snowflake Schema, Synthetic Keys, Circular References)
- Handling incremental loads and partial reloads
- Using variables and parameters in scripts

- Data Load Script – Script used to extract and transform data
- Resident Load – Loading data from an already loaded table
- Concatenate – Combining tables with similar fields
- Qualify / Unqualify – Handling field name conflicts
- Synthetic Key – An automatically created key due to multiple linking fields
- Circular Reference – A loop in table relationships

- Best practices for dashboard design
- Choosing the right chart types (Bar, Line, Pie, Scatter, Gauge, KPI, etc.)
- Using Master Items (Dimensions, Measures, Visualizations)
- Creating interactive filters (List Box, Dropdown, Slider, Search)
- Implementing Set Analysis for advanced filtering
- Using Bookmarks and Selections for user navigation

- Master Items – Reusable dimensions, measures, and visualizations
- Set Analysis – Advanced filtering syntax (e.g., ={$})
- Alternate States – Multiple selection states in the same app
- Bookmark – Saved selection state for quick access
- Storytelling – Creating guided analytics narratives

- Writing expressions using Aggregation Functions (Sum, Avg, Min, Max, Count)
- Using Conditional Functions (If, Pick, Match, etc.)
- Implementing Advanced Aggregations (Set Analysis, Aggr())
- Working with Date and Time Functions
- Creating Calculated Dimensions and Calculated Fields

- AGGR() – Nested aggregation function
- Set Analysis – Dynamic filtering in expressions (e.g., Sum({$} Sales))
- Calculated Dimension – A dimension derived from an expression
- Measure – A calculated metric (e.g., Sum(Sales))
- Variables – Storing reusable expressions (e.g., vTotalSales = Sum(Sales))

- Understanding Section Access for row-level security
- User roles in Qlik Sense (Admin, Developer, Analyst, User)
- Managing security rules in QMC (Qlik Management Console)
- Best practices for app security and governance
- Section Access – Script-based row-level security
- Data Reduction – Limiting data visibility based on user roles
- Stream – A folder-like structure for organizing apps
- Task – Scheduled reloads and distribution tasks

- Identifying and resolving performance bottlenecks
- Optimizing data models (reducing synthetic keys, minimizing joins)
- Using Qlik Sense Performance Analyzer
- Best practices for script optimization
- RAM Utilization – Monitoring memory usage
- Cache Management – Handling cached data for faster reloads
- QVD (Qlik Data File) – Optimized Qlik-native data storage format
- Partial Reload – Updating only changed data

- Publishing apps to the Qlik Sense Hub
- Sharing insights via Stories and Snapshots
- Exporting data and visualizations (Excel, PDF, Image)
- Using Qlik Sense Mobile for on-the-go analytics
- Publish – Making an app available to end-users
- Snapshot – A static image of a visualization with current selections
- Mashups – Embedding Qlik Sense apps in external websites
- Qlik Sense Mobile – Accessing dashboards on mobile devices

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Question: 504
When considering the impact of Qlik's Cognitive Engine on data analysis, which of the following features should be highlighted as beneficial for users?
1. Automatic suggestions for data visualization types based on data structure.
2. Enhanced loading speed for large datasets through optimization algorithms.
3. Predictive insights generated from historical data patterns.
Answer: A, C
Explanation: The Cognitive Engine offers automatic visualization suggestions and predictive insights, streamlining the analysis process and enhancing user experience.
Question: 505
When writing a data load script in Qlik Sense, which of the following statements accurately describes the purpose and capabilities of the script?
A. The script can extract data from multiple sources, such as databases, Excel files, and APIs.
B. It allows for data transformation, including filtering, aggregating, and renaming fields during the load process.
C. The script must be executed manually every time data is refreshed.
D. It can include conditional logic to load different data sets based on user inputs. Answer: A, B, D
Explanation: The data load script can extract from various sources, allows for transformations during loading, and can include conditional logic. However, scripts can also be scheduled for automatic execution.
Question: 506
4. Real-time collaboration tools for multiple users.
When loading data from multiple sources, what practices should be employed to ensure data integrity and consistency?
1. Standardize field names and data formats across different sources before loading.
2. Use the JOIN statement to combine records from different sources without common keys.
3. Validate data post-load to ensure accuracy and consistency.
4. Load data incrementally to avoid overwriting existing data.
Answer: A, C, D
Explanation: Standardizing names, validating data, and loading incrementally are important practices, while using JOINs without common keys can lead to data integrity issues.
In a scenario where you want to customize the colors of a bar chart based on performance metrics, which methods can be utilized to apply custom colors effectively?
A. Use the ColorMix function to create a gradient based on sales performance.
B. Specify CSS color codes directly in the color settings for specific measures.
C. Apply If statements in the color expression to change colors based on conditions.
D. Use the default color palette only, as custom colors are not allowed in Qlik Sense. Answer: A, B, C
Explanation: The ColorMix function allows for gradients, CSS color codes can be applied for specific measures, and If statements can dynamically change colors based on conditions, enhancing visualization.
Question: 508
In a scenario where you need to compare sales data across different regions while allowing for user interactivity, which methods should be utilized to facilitate effective comparisons?
A. Implementing filters to allow users to select specific regions.
B. Using bookmarks to save specific views of the data for quick access.
C. Applying alternate states to enable side-by-side data comparisons.
D. Utilizing set analysis to create predefined comparisons within visualizations.
Question: 507
Answer: A, C, D
Explanation: Filters allow for user selection of regions, alternate states enable side-by- side comparisons, and set analysis provides predefined comparisons, making these methods effective for interactive data analysis.
Question: 509
In a scenario where you want to calculate the difference in sales between the current month and the previous month, which expression would effectively achieve this?
1. Sum(Sales) where Month(DateField) = Month(Today()) - Sum(Sales) where Month(DateField) = Month(Today()) - 1
2. Sum({=$(=MonthStart(Today()))<=$(=MonthEnd(Today()))"}>} Sales) - Sum({=$(=MonthStart(AddMonths(Today(),
-1)))}<=$(=MonthEnd(AddMonths(Today(), -1))"}>} Sales)
Month(DateField) = Month(Today() - 1)
D. Sum(Sales) where DateField = Month(Today()) - Sum(Sales) where DateField = Month(Today()) - 1
Answer: B
Explanation: Option B correctly calculates the difference in sales between the current and previous months using Set Analysis to filter the respective date ranges.
Question: 510
When configuring the Qlik Management Console (QMC), which of the following tasks can an administrator perform?
A. Monitor application performance metrics and resource usage.
B. Create and manage user roles and security rules.
C. Develop new Qlik Sense applications directly from the QMC.
D. Schedule data reloads and manage data connections. Answer: A, B, D
Explanation: The QMC allows for monitoring performance, managing user roles and security, and scheduling data reloads, but application development occurs in the Qlik Sense Hub, not the QMC.
Sum(Sales) where Month(DateField) = Month(Today()) - Sum(Sales) where
Question: 511
To effectively utilize Bookmarks in Qlik Sense for a sales dashboard, which of the following practices should be avoided to maintain clarity and usability?
1. Creating descriptive names for each bookmark based on the selection criteria.
2. Saving bookmarks for each user-specific view of the data.
3. Organizing bookmarks into relevant folders for easy access.
4. Regularly updating bookmarks to reflect changes in data or analysis focus. Answer: B
Explanation: While saving user-specific views can be helpful, it may lead to clutter and confusion. It's better to maintain general bookmarks that apply broadly.
In the context of Qlik Sense, what are the benefits of utilizing web mashups within applications?
A. They enhance user engagement by integrating multiple data sources.
B. They allow embedding of external web content for enriched visualizations.
C. They limit the flexibility of Qlik dashboards by using static content.
D. They facilitate interactive experiences by combining Qlik data with web applications. Answer: A, B, D
Explanation: Web mashups enhance engagement and interactivity by integrating diverse data sources and embedding external content, improving the overall user experience.
Question: 513
When sharing insights through Snapshots in Qlik Sense, which of the following actions can enhance the clarity and effectiveness of the information presented?
A. Annotate Snapshots with comments explaining key insights.
B. Share Snapshots without context to allow users to interpret the data themselves.
C. Group related Snapshots in a Story for cohesive presentations.
D. Use high-resolution images to ensure visual clarity in presentations.
Answer: A,C,D
Question: 512
Explanation: Annotating Snapshots enhances clarity, grouping them in a Story provides a cohesive view, and using high-resolution images ensures visual clarity. Sharing without context is not advisable as it can lead to misinterpretation.
Question: 514
When analyzing customer feedback, which measures should be included in a Qlik Sense application to provide comprehensive insights?
1. Average feedback score for the period.
2. Total number of feedback submissions.
3. Customer demographics associated with feedback.
4. Percentage of positive feedback responses. Answer: A, B, C, D
positive feedback percentages allows for a complete analysis of customer feedback.
Question: 515
In your Qlik Sense application, you need to implement a conditional aggregation that counts the number of customers who made purchases over $500. Which of the following expressions would achieve this using the Count function?
A. Count({500"}>} Customers)
B. Count(If(PurchaseAmount > 500, Customers))
C. Count(Distinct Customers) where PurchaseAmount > 500
D. Count(Pick(Match(PurchaseAmount, >500), Customers)) Answer: B
Explanation: Option B correctly uses the Count function with an If condition to count only those customers whose purchases exceed $500.
Question: 516
When implementing a dashboard for analyzing employee performance, which measures should be included to provide comprehensive insights?
A. Total sales generated by each employee.
B. Average customer feedback score per employee.
Explanation: Including average scores, total submissions, customer demographics, and
1. Employee attendance records.
2. Overall team performance metrics. Answer: A, B, C, D
Explanation: Including total sales, average feedback scores, attendance records, and team metrics provides a well-rounded view of employee performance, enabling effective analysis.
Question: 517
To effectively use variables in Qlik Sense scripts, which of the following practices should be adopted?
1. Use the LET statement to define variables with expressions.
2. Reference variables in visualizations using the syntax =$(VariableName).
D. Regularly update variable values based on user interactions. Answer: A, B, D
Explanation: Defining variables with LET, referencing them in visualizations, and updating based on user interactions enhance the utility of variables in Qlik Sense.
Question: 518
In a Qlik Sense application, what best practices should be followed to ensure effective use of bookmarks?
A. Save bookmarks with descriptive names for easy identification.
B. Allow users to create personal bookmarks for their analysis.
C. Limit bookmark creation to ensure only essential views are saved.
D. Regularly review and manage bookmarks to remove outdated ones. Answer: A, B, D
Explanation: Saving bookmarks with descriptive names, allowing personal bookmarks, and regularly managing them enhance usability and organization within the application.
Question: 519
In preparing a Qlik Sense application for production, which of the following actions
Define variables only within the load script, not in expressions.
should be taken to ensure a professional appearance?
1. Create a clear and meaningful thumbnail image for the application.
2. Use a consistent color scheme throughout the application.
3. Include a detailed user manual as part of the app.
4. Set appropriate titles and labels for clarity in visualizations. Answer: A, B, D
Explanation: Creating a thumbnail, using a consistent color scheme, and setting clear titles and labels enhance the professional appearance of the application.
Question: 520
A. (Sum({} Sales) - Sum({} Sales)) / Sum({} Sales) * 100
B. (Sum(Sales) where Year = 2025 - Sum(Sales) where Year = 2024) / Sum(Sales) where Year = 2024 * 100
C. (Sum({} Sales) - Sum({} Sales)) / Sum({} Sales) * 100
D. (Sum(Sales) for Category = 'Electronics' in Year 2025 - Sum(Sales) for Category = 'Electronics' in Year 2024) / Sum(Sales) for Category = 'Electronics' in Year 2024 * 100
Answer: C
Explanation: Option C correctly applies Set Analysis to calculate the sales growth rate for the 'Electronics' category between 2024 and 2025.
Question: 521
What are Qlik Sense extensions, and in which situations should they be utilized to enhance application functionality?
A. Extensions are pre-built visualizations that can be used to extend the default capabilities of Qlik Sense.
B. Use extensions when you require a visualization type that is not provided by Qlik Sense natively.
C. Extensions should only be used for data loading purposes.
D. Extensions can be used to implement complex calculations that are not possible within standard visualizations.
To determine the sales growth rate compared to the previous year for a specific product category, which expression would you use to calculate this percentage change?
Answer: A, B, D
Explanation: Extensions enhance application functionality by providing additional visualization types and can be used for complex calculations when standard visualizations do not suffice.
Question: 522
To calculate the average revenue for each product category while excluding any categories with total sales less than $5,000, which expression would correctly use AGGR()?
1. Avg(Aggr(Sum(Sales), Category) where Sum(Sales) >= 5000)
2. Avg({5000"}>} Aggr(Sum(Sales), Category))
3. Aggr(Avg(Sales), Category) where Sum(Sales) >= 5000
Answer: A
Explanation: Option A correctly uses AGGR() to calculate the average revenue while filtering out categories with total sales below the specified threshold.
Question: 523
When discussing the benefits of using Qlik Core for developers, which of the following advantages should be highlighted?
A. Flexibility to embed analytics in custom applications
B. Pre-built dashboards for quick deployment
C. Access to Qlik's associative engine
D. Simplified data loading procedures Answer: A, C
Explanation: Qlik Core offers the flexibility to integrate analytics into custom applications and provides access to the powerful associative engine for data processing.
4. Avg(Aggr(Sum(Sales), Category) where Total Sales >= 5000)

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