QSBA2024 Practice Questions

A line chart is the most suitable visualization for this scenario. It is specifically designed to display trends of one or more measures over a continuous interval or time period. By plotting both Profit and Revenue as separate lines on the same chart, the business analyst can effectively compare their performance and identify patterns, trends, and relationships over time. The continuous x-axis represents time, and the y-axis represents the value of the measures, fulfilling all the requirements of the question.

B. Bullet chart: This chart is used to compare a single measure against a target and qualitative ranges (e.g., poor, average, good), not for comparing two measures over a time series.

C. Bar chart: While a bar chart can compare measures across time periods, it treats time as a discrete category, which is less effective for showing a continuous trend than a line chart.

D. Scatter plot: A scatter plot is used to visualize the relationship and correlation between two or three measures, not to track their individual trends over a continuous time dimension.

---

1. Qlik Sense for Windows Help, "When to use a line chart": "The line chart is suitable for showing trends over time. The dimension is always on the x-axis, and the measures are always on the y-axis... You can compare trends for different measures by including more than one measure in your chart."

2. Qlik Sense for Windows Help, "When to use a bullet chart": "The bullet chart lets you compare a measure's performance against a target. It is also possible to see how the measure performs in relation to a qualitative range."

3. Qlik Sense for Windows Help, "When to use a scatter plot": "The scatter plot helps you find potential relationships between values, and to find outliers in data sets. A scatter plot is used when you want to show the relationship between two or three measures."

The primary purpose of the master items library in Qlik Sense is to create reusable assets to ensure consistency and simplify app maintenance. The scenario explicitly states the Bar chart is "used in multiple sheets." Making it a master visualization allows the analyst to create it once and reuse it across the app. Any subsequent modifications to the master item will automatically propagate to all instances, which is the intended and most efficient use of this feature. The other visualizations (KPI, Treemap) are used only once, so the reusability benefit of making them master items is not applicable in this context.

A. Container: A Container is an object used to group other visualizations; it is not typically added to the master library for reuse in the same way as a chart.

B. KPI: The requirement states the KPI object is used only once, so there is no reusability advantage to making it a master item.

D. Treemap: The Treemap is used only a single time, which negates the primary benefit of creating a master visualization for reuse.

---

1. Qlik Sense on Windows Help, "Reusing visualizations with master items."

Section: Introduction.

Content: "If you want to reuse a visualization in other sheets, you can add it to the master items. ... This is useful when you want to have the same visualization on several sheets. When a master visualization is updated, the changes are applied everywhere the visualization is used." This directly supports creating a master item for the Bar chart which is used on multiple sheets.

2. Qlik Sense on Windows Help, "What are master items?"

Section: Master visualizations.

Content: "Master visualizations are charts that you can reuse in multiple sheets and for different purposes. A master visualization can be a chart that you have created, or a chart that is linked to a master visualization." This reference defines master visualizations by their reusability, which is the key factor in the question.

The requirement is to calculate a value "regardless of selections." In Qlik's Set Analysis syntax, the identifier 1 is used to represent the entire set of records in the data model, thereby ignoring any selections made by the user. The expression Sum({1} Sales) correctly calculates the sum of the Sales field over all records in the application. While the full expression to meet the request would also need a modifier for the year (), this option correctly uses the identifier required to ignore selections.

A. Sum( { } Sales)

This is syntactically incorrect. A set expression requires an identifier (like 1 or $) within the curly braces {} to define the record set to be evaluated.

B. Sum( { $ } Sales)

The $ identifier represents the current user selections. This expression is equivalent to Sum(Sales) and would change as the user makes selections, which is the opposite of the requirement.

D. Sum( 1 { } Sales)

This is syntactically incorrect. The set identifier 1 must be placed inside the curly braces, not outside of them.

---

1. Qlik Sense for Developers - Second Edition (2021), by Miguel Ángel García and Barry Harmsen. Chapter 6: Set Analysis, Section: "Set identifiers". The book explains: "The number 1 as a set identifier represents the full set of records in the application, ignoring any selections." (This is a conceptual reference as direct page numbers for digital editions vary, but the concept is fundamental in the Set Analysis chapter).

2. Qlik Sense Official Help Documentation, "Set analysis and set expressions". In the section "Set identifiers," the documentation explicitly states:

1: "Represents the full set of all the records in the application, irrespective of any selections made."

$: "Represents the records of the current selection. The expression sum(Sales) is equivalent to sum({$} Sales)."

This directly supports that 1 is used to ignore selections and $ respects them.

3. Qlik Sense Official Help Documentation, "Syntax for set expressions". This section outlines the correct structure of a set expression as { identifier { operator modifier } }, confirming that identifiers like 1 and $ must be placed within the curly braces, rendering options A and D syntactically invalid.

A network chart is the ideal visualization for this scenario. It is specifically designed to represent entities (nodes) and the relationships between them (links or edges). In this case, the project tasks and subtasks are the nodes, and their co-dependencies are the links. The network chart allows for complex, non-hierarchical relationships, which is crucial for co-dependent tasks. Furthermore, it supports customizing the visual properties of the nodes, such as coloring the boxes based on the project or task status, directly fulfilling all the business analyst's requirements.

A. Sankey chart: This chart visualizes the magnitude of flow between nodes, not the structural relationships or co-dependencies of tasks in a project workflow.

B. Grid chart: This is a matrix-based visualization that uses color to represent values across two dimensions. It cannot show connections or dependencies between items.

C. Org chart: This chart is designed for strict, top-down hierarchical structures and cannot represent the complex, many-to-many dependencies common in project tasks.

1. Qlik Sense for Windows Help, "Network chart" section: "The network chart displays a diagram of nodes and links to show relationships in data... You can set the size and color of the nodes, and the thickness and color of the links, based on measures." This directly supports using a network chart to represent tasks (nodes) and their relationships (links) and coloring them by status (a measure).

2. Qlik Sense for Windows Help, "When to use an organization chart" section: "The organization chart is used to show hierarchical structures, such as a company's organization or a family tree." This confirms its unsuitability for non-hierarchical, co-dependent tasks.

3. Qlik Sense for Windows Help, "When to use a Sankey chart" section: "The Sankey chart is used to visualize the magnitude of flow between nodes in a network." This highlights its focus on flow quantity rather than structural dependency.

4. Healy, K. (2019). Data Visualization: A Practical Introduction. Princeton University Press. Chapter 6, "Draw a network": This chapter describes network graphs (or charts) as the standard method for visualizing entities and their connections, which is the core requirement of the question. It distinguishes them from hierarchical charts like tree diagrams (or org charts). (Note: While a general academic source, its principles are directly applicable and foundational to the visualization capabilities in tools like Qlik).

This combination of charts directly addresses the four analytical requirements. An org chart is specifically designed to visualize hierarchical data like a company's employee structure. A bar chart is ideal for comparing a measure (average salary) across a categorical dimension (region). A map chart is the standard and most effective way to display geographical data, such as office locations and their capacity. Finally, a line chart is the best practice for showing trends and changes in a measure (company retention) over a continuous period, such as time.

A: A sankey chart is used to visualize flows and their magnitudes between nodes, not a formal hierarchical structure like a company organization.

B: While a network chart can show relationships, an org chart is the specific and more appropriate visualization for a formal, top-down employee structure.

C: A grid chart is used for visualizing measures across two dimensions, and a KPI object shows a single key performance indicator, neither of which is suitable for the specified requirements.

1. Org chart: Qlik Sense® on Windows Help, "Visualizations: Org chart". The documentation states, "The organization chart (Org chart) is good for showing hierarchical data, such as a company's organizational structure or a file system." This directly supports its use for "Company employee structure".

2. Bar chart: Qlik Sense® on Windows Help, "Visualizations: Bar chart". The documentation specifies, "The bar chart is suitable for comparing values between different groups or categories." This aligns with comparing "Average employee salary by region".

3. Map chart: Qlik Sense® on Windows Help, "Visualizations: Map". The documentation notes, "The map is used to show geographical data and present it with your measure values." This is the correct choice for a "Geographical representation of office capacity".

4. Line chart: Qlik Sense® on Windows Help, "Visualizations: Line chart". The documentation states, "The line chart is mainly used to show trends over time." This makes it the ideal chart for visualizing "Company retention over time".

Set analysis is the most appropriate Qlik Sense feature for this scenario. It allows a business analyst to create specific expressions within visualizations that define a data scope independent of the user's current selections. By using set analysis, the analyst can build different charts or tables on the same or different sheets, each tailored to a customer's unique analytical objective. This approach maintains a single app and a single data model, ensuring efficiency, consistency, and ease of maintenance while providing customized analytical views for each customer.

A. Apply Section Access to manage the data for each customer

Section Access is a security feature for row-level data reduction, not a tool for tailoring analysis. It would restrict what data users are allowed to see, which is not the primary requirement here.

C. Duplicate and rename the apps for each customer

This creates significant maintenance overhead. Any change to the data model or a master visualization would need to be replicated in every duplicated app, which is inefficient and error-prone.

D. Unpivot, then re-associate the data tables for each customer

Unpivoting is a data transformation technique used in the load script. It addresses the structure of the data model, not the creation of different analytical views for end-users within the app interface.

---

1. Qlik Sense® for Windows Help, "Using set analysis" section.

Reference: "Set analysis offers a way of defining a set of data values that is different from the normal set defined by the current selections in an app. This is useful when you want to make comparisons between data sets, for example, to compare sales for the current year with the previous year, or to compare a selected region's sales with the total for all regions." This directly supports using set analysis to create different analytical views (comparisons/subsets) for different objectives.

2. Qlik Sense® for Windows Help, "Managing security with section access" section.

Reference: "You can use section access to control the security of an app. It allows you to control what data and what features users can access when they open an app... Section access is applied to the data in an app, restricting user access to specific data rows and columns." This confirms that Section Access is a security/governance tool, making it less suitable for the stated goal of meeting "analysis objectives."

3. Henric Cronström, Qlik Principal Enterprise Architect, "App Proliferation" (Qlik Community Blog).

Reference: While not a formal document, this blog by a Qlik expert articulates a widely-held best practice. It explains the problems of app duplication: "The main problem with app proliferation is maintenance. If you need to change a formula, a master item, or a variable, you will have to do it in all apps... This is both tedious and error-prone." This supports the reasoning for why option C is incorrect.

4. Roche, D. (2019). Mastering Qlik Sense. Packt Publishing.

Reference: Chapter 7, "Advanced Expressions and Set Analysis," explains that set analysis allows developers to "define the scope of an aggregation, completely independent of the selections made by the user." This capability is the foundation for creating visualizations that cater to different, pre-defined analytical objectives as required by the question.

The Section Access table controls data visibility. USER1, with an ACCESS level of 'USER', is linked to SACOUNTRY values 'France' and 'Spain' across two rows, granting access to data from both countries. USER2, also a 'USER', is linked only to 'United Kingdom' and will see data for that country exclusively. The USERID 'ADMIN' is assigned the 'ADMIN' ACCESS level. This level grants the user complete access to all data within the application, bypassing any data reduction fields. Therefore, the ADMIN user will see data for all countries present in the data model: France, Spain, United Kingdom, and Germany.

B: This is incorrect because the table explicitly grants access to USER1 and USER2 for the specified countries, it does not deny it.

C: This is incorrect as users are granted access, and the ADMIN user is correctly configured and would not be locked out of the application.

D: This is incorrect because it wrongly limits the ADMIN's view. The 'ADMIN' access level provides visibility to all data, including Germany, not just the values listed in the table.

---

1. Qlik Sense for Administrators Help: Managing security with section access. This official documentation details the function of the ACCESS column. It states, "The access levels are ADMIN and USER. ADMIN access is given to users who should have access to all data in the app... USER access is given to users who should have access to only selected data in the app..." This confirms why the ADMIN sees all data and USERs see reduced data.

2. Qlik Sense for Administrators Help: Managing security with section access > The section access table. The documentation explains how multiple rows for a single user are handled: "If you want to grant a user access to several field values, you enter one row for each value." This supports the outcome for USER1, who is granted access to both 'France' and 'Spain'.

3. Qlik Sense for Developers Help: Section access. This page reinforces the concept of data reduction for the 'USER' level: "When a user with USER access opens an app, Qlik Sense uses the data in the section access table to determine which data to show the user." This directly applies to the scenarios for USER1 and USER2.

The most effective and efficient solution is to use a variable controlled by a slider. Variables in Qlik Sense act as dynamic placeholders whose values can be changed by users in real-time without requiring a data reload. By linking a variable to a slider object, users can intuitively adjust the threshold value. The visualization's color expression can then reference this variable (e.g., If(Sum(Profit) < $(vProfitThreshold), 'red', 'green')). This approach provides each user with a personalized, interactive experience, which is ideal for "what-if" analysis and aligns perfectly with the requirements.

A. A filter pane operates on existing field values within the data model. This would require pre-defining a list of thresholds, preventing users from inputting their own specific values.

B. This is highly inefficient as the app's data only changes daily. Frequent reloads are unnecessary, and a shared spreadsheet would not allow for individual user-defined thresholds.

D. The Bucket function is a data load script function that creates static, pre-defined ranges. It does not allow for dynamic adjustment by the user within the published application.

---

1. Qlik Sense for Windows Help, "Using variables in expressions": This official documentation explains that variables can be used to support "what-if analysis." It explicitly states, "You can use specific objects to change the value of a variable dynamically in an app," which directly supports the use of a slider or input box to control a variable's value post-reload. (Accessed via Qlik Sense for Windows Help, section: Creating visualizations > Using expressions > Using variables in expressions).

2. Qlik Sense for Windows Help, "Dashboard bundle": The documentation for the Dashboard bundle describes the "Variable input" control, which can be rendered as a slider. It states this object "lets you set the value of a variable," confirming it is the standard tool for implementing the functionality described in the correct answer. (Accessed via Qlik Sense for Windows Help, section: Creating visualizations > Bundles > Dashboard bundle).

3. Qlik Sense for Windows Help, "Bucket - script and chart function": This page details that the Bucket function is used during the data load script to classify numeric values into discrete text-based ranges. This confirms it is a static transformation and cannot be altered by the end-user in the analysis view, making option D incorrect. (Accessed via Qlik Sense for Windows Help, section: Scripting > Script syntax and chart functions > Logical functions > Bucket).

In Qlik Sense, a hyphen (-) displayed in a filter pane is the default visual representation for null values. Null values signify that data is missing or non-existent in the source for a particular field. The number 6 appearing next to the hyphen indicates that there are exactly six records (in this case, movies) in the dataset that have a null or empty value for the Length Range field. By selecting the hyphen, the analyst isolates these six records, confirming that their length data is missing.

A. The hyphen represents a null/missing value by default in Qlik Sense, not an "illegal character" contained within the source data itself.

B. This is a broad historical inference. Selecting records with missing data does not provide any information about the length variance of other movies.

C. This is an unsubstantiated generalization. The selection only confirms that six specific movies have missing data, not that all movies from entire decades do.

1. Qlik Sense® on Windows Help. (2024). Handling NULL values in Qlik Sense. QlikTech International AB.

Reference Details: In the section "How NULL values are interpreted," the documentation states, "When data that contains NULL values is loaded into Qlik Sense, the NULL values will result in that no value, or a special NULL value character, is displayed, depending on the context." The hyphen in a filter pane is this special character representation for missing data.

2. Qlik Sense® on Windows Help. (2024). NullAsValue. QlikTech International AB.

Reference Details: The documentation for the NullAsValue script statement explains that by default, "Qlik Sense treats NULL values found in a table as missing or undefined." This confirms that the underlying data state for the records represented by the hyphen is "missing," which directly supports the correct answer.

To optimize app performance, the primary goal is to reduce the amount of data loaded into Qlik's in-memory engine. This involves reducing both the number of columns (fields) and rows (records).

Option D provides the most effective and appropriate strategy. Deselecting the Cardholder and other unnecessary fields reduces the width of the data model. Applying a filter during the data extraction process to only load the last two years of transactions significantly reduces the number of rows, which is the most impactful performance improvement. Finally, in a managed Qlik Sense environment, scheduling automated daily reloads is an administrative task performed in the Qlik Management Console (QMC), so requesting this from a system administrator is the correct procedure.

A. Bookmarks and sheet-level reloads do not reduce the amount of data loaded into the app's memory; they only affect the user's view or perform a manual, one-time data refresh.

B. Set analysis performs calculations on data already loaded in memory. It does not reduce the initial data volume and therefore does not improve the app's load performance or memory footprint.

C. A filter pane, like a bookmark, is a user interface object for filtering data already present in the app. It does not reduce the size of the in-memory data model.

---

1. Filtering Data During Load & Deselecting Fields:

Qlik Sense® for Windows Help, "Best practices for data modeling," Section: "Reduce the amount of data". This official guide states, "The best way to make an application more efficient is to make sure that you only load the data you actually need for your analysis... Remove unused fields and tables... Filter data that is not needed in the app using WHERE clauses." This supports deselecting fields and applying a filter to extract only the required years.

2. Scheduling Reloads:

Qlik Sense® for Windows Help, "Administering Qlik Sense Enterprise on Windows," Section: "Managing reloads". The documentation specifies, "You create and manage reload tasks in the Qlik Management Console (QMC)." This confirms that scheduling is an administrative function, separate from the app development interface (Data Manager), making the request to a system admin the correct workflow for a business analyst.

3. Performance Impact of Data Reduction:

Qlik Sense® for Windows Help, "Performance and scalability in Qlik Sense Enterprise," Section: "Data model". The documentation emphasizes, "The amount of data loaded into a Qlik Sense app affects its performance... Reducing the amount of data in the app is the most effective way to improve performance." This validates that the core strategy in option D (reducing rows and columns at load time) is the most effective for performance.