The business requirement is to count the number of unique rodents that have participated in at least one maze experiment. The MazeEscapes table serves as a fact table, recording every attempt. A single rodent can have multiple entries in this table. Therefore, to find the number of unique rodents who have made attempts, we must count the distinct RodentID values present in the MazeEscapes table. The expression Count(Distinct RodentID) correctly performs this aggregation, counting each rodent only once, regardless of how many attempts they have made.

B: This calculates the total number of rodents in the master Rodent table, not the number of rodents who have actually attempted a maze.

C: This calculates the total number of maze attempts by summing a '1' for each row in the MazeEscapes table, not the number of unique rodents.

D: This also calculates the total number of rodents in the master Rodent table, which is not what the business analyst needs to measure.

1. Qlik Sense for Windows Help, Count - chart function: The official documentation specifies the use of the distinct qualifier. It states, "If the word distinct occurs before the expression, all duplicates are disregarded." This directly supports using Count(Distinct RodentID) to find the number of unique participants.

Source: Qlik Sense on Windows Help, Document ID: QlikSenseonWindowsMay2024, Section: Visualizations > Expressions > Chart functions > Aggregation functions > Count - chart function.

2. Qlik Sense for Windows Help, Best practices for data modeling: This documentation explains the fundamental concept of fact and dimension tables. The MazeEscapes table is a transactional (fact) table, and the Rodent table is a dimensional (master data) table. To analyze events or transactions (like maze attempts), aggregations must be performed on the fact table. This principle invalidates options B and D, which incorrectly query the dimension table for this specific KPI.

Source: Qlik Sense on Windows Help, Document ID: QlikSenseonWindowsMay2024, Section: Preparing data > Best practices for data modeling > Star schema.

3. Qlik Sense for Windows Help, KPI: The documentation on creating KPIs shows that the primary component is the "Measure," which is defined by an expression. The expression Count(Distinct RodentID) is a valid measure for a KPI object designed to show a single, key performance indicator like the number of active rodents.

Source: Qlik Sense on Windows Help, Document ID: QlikSenseonWindowsMay2024, Section: Visualizations > KPI > Properties > Data > Measures.

The most robust and scalable method to meet the requirements is to integrate the group-level security directly into the Section Access script. By adding the Group field to the Section Access table, a direct link is created between the logged-in user (Sales Account ID) and their assigned Group. When the user opens the app, Section Access automatically reduces the data model, so the Group field will only contain the single value associated with that user. This allows for a simple and efficient conditional expression on each sheet's "Show condition" property (e.g., Only(Group) = 'GroupA') to control its visibility, fulfilling the requirements securely and efficiently.

A. Use the Sales Account ID as a filter on the show/hide condition on the relevant sheet

This approach is not scalable. It would require manually listing all Sales Account IDs for each group within each sheet's show condition, making it difficult to maintain.

B. Use the Group as a filter on the show/hide condition on the relevant sheet

This is a partial solution. While the condition would use the Group field, this option fails to specify how the application will associate the logged-in user with their specific group.

D. Use the OSUser() function within the show/hide condition of the sheets to set the required visibility

The OSUser() function typically returns the service account running the reload, not the end-user accessing the app. Even with the correct function (e.g., UserID()), performing this logic in the UI is inefficient.

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1. Qlik Sense for Administrators Help - Managing security with section access:

Section: How section access works

Content: The documentation explains that Section Access works by dynamically reducing data based on the user's credentials defined in the load script. By including a field like Group in the Section Access table, Qlik links the user to that data value. This reduced data set is then used throughout the app, making it the authoritative source for security-driven logic, including sheet visibility. This supports adding Group to the Section Access table as the primary step.

Source: Qlik Sense Enterprise on Windows Help, "Managing security with section access".

2. Qlik Sense for Business Analysts Help - Conditional show of sheets, visualizations, dimensions, and measures:

Section: Conditional show of sheets

Content: This official guide details how to use the "Show condition" property for sheets. It states, "You can show or hide a sheet dynamically, depending on a condition... For example, you can use this feature to show a sheet only when certain values are present in your data, or if a user belongs to a certain user group." This directly supports the second part of the correct answer: applying the Group field (which is now filtered by Section Access) to the sheet's show condition.

Source: Qlik Sense Enterprise on Windows Help, "Conditional show of sheets, visualizations, dimensions, and measures".

The Employees and InternEmp tables represent the same logical entity: company personnel. They share a nearly identical structure, with fields for ID, name, title, and hire date. According to data modeling best practices, when two or more tables contain the same kind of data, they should be combined into a single table. The correct operation for this is concatenation, which appends the rows of one table to another. This creates a single, unified dimension table for all employees, simplifying the data model, preventing potential synthetic keys, and enabling straightforward analysis across both permanent and temporary staff. The Qlik Sense Data Manager is designed to perform this operation, often automatically.

A. Create a concatenated key to associate the Employees and InternEmp tables

A concatenated (or composite) key is used to form a unique identifier from multiple fields for linking tables, not for merging two lists of the same entity.

C. Force an association between the InternEmp and the Orders tables

This is incorrect as there is no logical basis for directly associating interns with orders without first integrating the employee data into a single, coherent dimension.

D. Create an association between the EmpID and EmployeelD fields

This is a common pitfall. While the Data Manager recommends this association based on field name similarity, it is logically incorrect. EmpID and EmployeeID are primary keys for two distinct sets of people. Associating them would incorrectly link unrelated individuals and create a flawed data model.

1. Qlik Sense for Windows Help, "Concatenating tables in Data Manager": This official documentation states, "When you add two or more tables that have the same number of fields and identical field names, Qlik Sense automatically concatenates them into a single table." This confirms that concatenation is the intended and standard procedure for the scenario described. The document further explains how to manually align fields to force concatenation if they are not identical, which would be necessary for EmpID and EmployeeID.

2. Qlik Sense for Windows Help, "Best practices for data modeling": This guide emphasizes creating simple and logical data structures, such as star schemas. Concatenating the two employee tables into a single Employee dimension table aligns with this best practice. It avoids the creation of a "snowflake" or a more complex, incorrect association between two parts of the same dimension. Section: "Keep your data model simple".

Qlik Alerting is the feature designed specifically for this use case. It allows a business analyst to configure data-driven alerts that actively monitor key performance indicators (KPIs). When the data crosses a predefined threshold, the system automatically triggers and sends a notification to specified users, such as the director, via email or the Qlik Sense mobile app. This proactive approach ensures that stakeholders are informed of critical changes in real-time without needing to be logged into the application, which is ideal for a director with limited time.

A. Weekly PDF report: This is a scheduled, static report. It does not provide immediate notification when a threshold is breached but only at a fixed interval.

B. Storytelling: This is a presentation feature within Qlik Sense used to build a narrative around data. It requires the user to actively open and view the story.

D. Bookmark: A bookmark saves a specific set of selections or a state within an application for later analysis. It is not a notification mechanism.

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1. Qlik Sense on Windows Help: Alerting. "With data alerting, you can easily monitor your charts and be notified when data changes. You can create alerts for charts in your apps. When the conditions for the alert are met, you are sent a notification." This directly supports the use of alerts for threshold-based notifications.

2. Qlik Sense on Windows Help: Creating an alert. This section details the process of setting up an alert, which includes defining a measure and setting a condition (e.g., "Value is greater than," "Value is less than"). This directly corresponds to the "threshold is breached" requirement in the question.

3. Qlik Sense on Windows Help: Distributing reports with subscriptions. This documentation explains that subscriptions are used to "regularly schedule a report for export and delivery." This confirms that reporting is time-based, not event-driven, making it unsuitable for the scenario.

4. Qlik Sense on Windows Help: Sharing insights with data storytelling. This source describes storytelling as a feature to "combine reporting, presentation, and exploratory analysis." It is an in-app presentation tool, not a proactive notification system.

The requirements for the two teams are fundamentally different. The internal analyst team needs a comprehensive, detailed application for deep analysis, which is best suited for a desktop experience. The sales team needs a streamlined, simplified, and touch-friendly application optimized for mobile devices, focusing on key performance indicators.

Creating two separate apps allows for a purpose-built user experience for each group without compromise. The mobile app can be designed with a single-column layout and fewer objects for clarity and performance, while the desktop app can provide the complex, multi-chart "global view" the analysts require. Both apps can leverage the same underlying data model to ensure consistency.

A. One app with a specific extension for mobile users: An extension cannot fundamentally alter a complex app's layout to make it suitable for a small screen; it only adds specific functionality.

C. A mashup with various objects: A mashup still faces the same design challenge of serving two different experiences and would likely require separate, tailored web pages, making it a more complex solution.

D. One app with various objects: A single, complex app designed for a "global view" will be cluttered and difficult to use on a mobile device, even with Qlik's native responsive capabilities.

1. Qlik Sense® on Windows Help: In the section on creating visualizations, the documentation provides guidance on responsive design. It explicitly states, "For small screens, it is a good practice to design the sheets with a single column layout" and to "Limit the number of visualizations on a sheet." This advice for mobile design directly conflicts with the requirements for a "global view" for analysts, supporting the need for a separate, optimized mobile app.

Source: Qlik Sense® on Windows Help, "Creating visualizations" -> "Building responsive apps" -> "Tips for creating responsive layouts".

2. Qlik Sense® on Windows Help: The best practices for app design emphasize tailoring the application to the intended audience and their needs. When audiences have conflicting needs, such as deep exploration versus quick mobile access, creating separate, targeted apps is the standard approach to ensure usability and adoption for both groups.

Source: Qlik Sense® on Windows Help, "Creating apps and visualizations" -> "Best practices for designing apps".

The scenario requires a solution that provides both a high-level overview and enforces strict data segregation by region. A dashboard is the standard Qlik Sense feature for creating a high-level sheet with key performance indicators (KPIs) that can navigate to detailed sheets. Section Access is the designated Qlik Sense security feature for implementing dynamic data reduction at the row level. It ensures that when a user from a specific regional team opens the app, the data is automatically and securely filtered to show only their region's data, fulfilling the critical security requirement that users "should only have access to the data in their region."

B. A pivot table that filters by region: A user-applied filter is not a security measure; users could change the filter to view data from other regions, violating the access requirement.

C. A Multi KPI with set analysis: Set analysis defines the scope of a calculation within a chart but does not restrict a user's access to the underlying data in the app.

D. A dashboard with regional bookmarks: Bookmarks are saved selection states for convenience. They do not enforce security and can be cleared, allowing users to select and view unauthorized data.

1. Qlik Sense® for Windows Help, "Managing security with section access": This official documentation states, "You can use section access to control the security of an app. It allows you to define an authorization table in the data load script to control which users can see what data." This directly supports the use of Section Access for the regional data segregation requirement.

2. Qlik Sense® for Windows Help, "How section access works": This section details the mechanism: "When a user opens an app, Qlik Sense authenticates the user... and compares this identity to the authorization table. If the user is authorized, the data is reduced based on the security table entries, and they can access the app." This confirms it is the correct feature for enforcing access rules.

3. Qlik Sense® for Windows Help, "Best practices for dashboard design": This document outlines the purpose of a dashboard as providing an "at-a-glance view of key performance indicators" and enabling users to "drill down into the data for more details," which aligns with the requirement for a high-level sheet that navigates to detail sheets.

Qlik Sense storytelling is the feature designed specifically for creating data-driven presentations. It allows a business analyst to build a narrative using snapshots of visualizations to emphasize key points, meeting the "emphasize important sales revenue" requirement. Crucially, a story can contain embedded, live sheets from the app. This enables the CEO to switch from the presentation view to the interactive sheet to explore data and answer audience questions dynamically. Publishing the app makes the story available as shared content, fulfilling all stated requirements for the presentation.

A. Embed a video player in the shared app with a recording to describe the charts: A pre-recorded video is static and does not permit the dynamic data exploration needed to answer audience questions live.

B. Create a sheet that features colorful and layered visualizations and export as a PDF: A PDF is a static document. It cannot be used to dynamically answer questions from the audience during the presentation.

C. Set up NPrinting to connect to the app and design a slideshow-style report: NPrinting generates static reports (e.g., PowerPoint, PDF). While it can create a slideshow, it lacks the live, interactive capability required for dynamic questioning.

1. Qlik Sense on Windows Help, "Building stories" section: This official documentation explicitly states, "You can also add sheets from the app to your story. The sheets are live and interactive, and you can make selections in them." This directly supports the capability to answer questions dynamically.

Source: Qlik Sense® on Windows Help, "Data storytelling," subsection "Building stories."

2. Qlik Sense on Windows Help, "Presenting a story" section: This page describes the presentation process and highlights the ability to interact with the underlying data. It notes that when presenting a story with a live data sheet, you can "make selections and analyze your data as you would on the sheet itself." This confirms the feature's suitability for dynamic Q&A.

Source: Qlik Sense® on Windows Help, "Data storytelling," subsection "Presenting a story."

The requirement is to maintain consistent colors for the same dimension values across two different charts. The standard and most efficient way to achieve this in Qlik Sense is by using the built-in coloring properties. Setting the coloring to 'By Dimension' instructs the chart to assign a unique color to each value of the dimension. Enabling the 'Persistent colors' option ensures that this color-to-value mapping is stored and applied consistently across all other charts within the same application that use the same dimension and setting.

A. Use nested IF statements to set the colors by expression for each dimension value

This method is inefficient, not scalable, and difficult to maintain. It requires manually hard-coding a color for each dimension value, which must be updated if new values appear.

B. Define the color values in the master measures and use the color library

This is incorrect because the requirement is to color by the dimension (Customer Name), not the measure (Total Sales, Number of Orders). Master measure coloring applies to the measure itself.

D. Use the Fieldlndex function to set the colors by expression for each dimension value

While this is a more dynamic expression than nested IFs, it is more complex than the standard UI option. Furthermore, the color assignment depends on the data load order, which may not be consistent.

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1. Qlik Sense for Windows Help, "Coloring a visualization" section: This official documentation details the coloring options available in the properties panel. It explicitly states for the 'Persistent colors' checkbox: "Select to have the colors for the dimension values be persistent across all visualizations in an app." This directly supports the chosen answer as the intended method for achieving color consistency for a dimension across multiple charts. (Accessed via Qlik Sense SaaS Help, Visualizations > Customizing a visualization > Changing the appearance of a visualization > Coloring a visualization).

2. Qlik Sense for Windows Help, "Properties panel" section: Under "Appearance > Colors and legend," the documentation describes the 'Colors' setting. When set to 'Custom' and 'By dimension', it allows for the selection of 'Persistent colors', confirming this is the correct location and combination of settings to perform the required action. (Accessed via Qlik Sense SaaS Help, Visualizations > Properties panel > Appearance properties).

The primary cause of slow performance is the execution of row-level string functions (Left, Trim, Right) and arithmetic operations within a front-end chart expression on a very large dataset (10 million rows). These calculations are performed every time the app state changes. The most effective Qlik performance optimization strategy is to move these transformations and calculations from the chart expression into the data load script. By pre-calculating the required values during the data load, the results are stored directly in the data model. The front-end KPI then only needs to perform a simple aggregation on this pre-calculated field, which is significantly faster and less resource-intensive. Option B correctly describes this best practice using the Data Manager.

A. This proposes an external solution outside the Qlik business analyst's control and does not use Qlik Sense capabilities to resolve the immediate performance issue within the app.

C. This keeps the calculation in the front-end master measure. While SubField might be slightly more efficient than nested functions, it does not solve the core problem of performing row-level calculations at runtime.

D. This action only modifies the string and does not create the final calculated numeric field. The front-end expression would still need to parse the modified string, failing to offload the calculation to the script.

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1. Qlik Sense® on Windows Help, "Tips for improving app performance", section "Move calculations to the data load script". This official documentation explicitly states: "Calculations that you make in chart expressions are made every time you make a selection in the app. This can affect the response times in your app. To improve performance, you should move calculations to the data load script when possible." This directly supports the methodology described in the correct answer.

2. Qlik Sense® on Windows Help, "Managing data with Data manager", section "Adding a calculated field". This document outlines the procedure for creating new fields based on calculations during the data preparation stage, which is a core part of the solution in option B. It confirms that a business analyst can perform this task using the Data Manager interface.

3. Qlik Sense® on Windows Help, "Managing data with Data manager", section "Splitting a table field". This source details how to use the Split transformation in the Data Manager to parse a single field into multiple fields based on a delimiter, which is the first step described in the correct answer.