Pass the Qlik Sense Business Analyst QSBA2024 Questions and answers with ExamsMirror

The InternEmp table contains information about temporary employees (interns), and the Employees table contains regular employee data. To properly link these two tables, the business analyst needs to create an association between theEmpIDin theInternEmptable and theEmployeeIDin theEmployeestable. This will ensure that the two tables are correctly associated based on the employee identifiers, allowing the system to relate both tables in the data model.

Key Concepts:

Association: Qlik Sense automatically suggests associations between tables based on field names. By linkingEmpIDfrom InternEmp withEmployeeIDfrom Employees, the tables can be properly related in the data model.

Association View: The association view in Data Manager helps visualize how tables are connected and suggests appropriate links between tables based on common fields.

Why the Other Options Are Less Suitable:

A. Create a concatenated key: Concatenation is unnecessary for this scenario since the data model relies on direct associations between keys.

B. Concatenate the tables: Concatenating the InternEmp table into the Employees table would combine the records, but it’s not appropriate since the two tables should remain separate entities.

C. Force an association between InternEmp and Orders: There’s no need to associate InternEmp with Orders directly since the focus is on employees and interns.

References for Qlik Sense Business Analyst:

Field Associations in Qlik Sense: Properly associating fields between tables is crucial for building a clean and efficient data model in Qlik Sense.

Thus, creating an association betweenEmpIDandEmployeeIDis the best approach, makingDthe correct answer.

For this scenario, using abar chart,scatter plot, andhistogramprovides the best coverage of the requirements. Thebar chartis ideal for comparing the sales performance of the top 10 sales representatives. Thescatter plotis used to analyze the relationship between margin percentage and total sales by product category. Thehistogramis excellent for visualizing the distribution of sales amounts.

Key Concepts:

Bar Chart: Perfect for comparing categorical data, such as sales amounts across different sales representatives.

Scatter Plot: Ideal for exploring relationships between two variables, such as margin percentage and total sales.

Histogram: Provides a clear visualization of the distribution of a continuous variable, such as sales amounts.

Why the Other Options Are Less Suitable:

B. Treemap, Container, and Distribution plot: A treemap is less effective for comparing individual sales reps, and a container does not provide a clear visualization on its own.

C. Bar chart, Line chart, and Scatter plot: A line chart is not needed in this case, as it is best for showing trends over time, which is not required here.

D. Treemap, Box plot, and Histogram: A box plot is more suited for showing statistical distributions (e.g., quartiles), which is unnecessary in this case.

References for Qlik Sense Business Analyst:

Data Exploration: Bar charts, scatter plots, and histograms are among the most commonly recommended visualizations for comparing performance, analyzing relationships, and viewing distributions in Qlik Sense.

Thus, the combination of abar chart,scatter plot, andhistogramoffers the most comprehensive solution, makingAthe correct answer.

Ascatter plotis the best choice for visualizing outliers, clustering, and products that are above the median sales volume. Scatter plots are excellent for showing relationships between two variables (like sales volume and margin %) while providing the ability to highlight outliers. By usingK-Means clusteringto color the products, the business analyst can visually group similar products. Additionally, adding amedian sales volume reference linemakes it easy to identify which products are above or below the median.

Key Concepts:

Scatter Plot: This visualization is ideal for detecting outliers and understanding the distribution and clustering of data points.

K-Means Clustering: This technique groups similar data points (products) based on their values, which helps to identify patterns visually.

Median Reference Line: Adding a reference line for median sales volume ensures that the analyst can easily see which products are performing above or below the median.

Why the Other Options Are Less Suitable:

A. Pivot table: While a pivot table could show aggregated data, it is not as effective for visualizing outliers or clustering as a scatter plot.

B. Treemap: A treemap can show hierarchical relationships but is not as effective for identifying clusters or outliers.

C. Combo chart: A combo chart is not as well-suited for visualizing clustering and outliers as a scatter plot.

References for Qlik Sense Business Analyst:

Outliers and Clustering Visualization: Qlik Sense recommends scatter plots for visualizing relationships between two measures and for detecting outliers and clustering in the data.

Thus, creating ascatter plotwith K-Means clustering and a median sales volume reference line is the best approach, makingDthe verified answer.

In Qlik Sense, the'By Dimension'and'Persistent colors'options in the Colors property panel ensure that the same dimension values have the same color across multiple charts. This is especially useful when you have two or more side-by-side charts sharing a common dimension, like customer names in this case. Persistent colors guarantee consistency in color assignment, helping users visually track the same dimension across different visualizations.

Key Concepts:

By Dimension: This option ensures that each unique value of a dimension (e.g., customer name) gets a distinct color across all charts that use this setting.

Persistent Colors: This feature ensures that the colors remain the same between charts, making the visual comparison across charts easier for the users.

Why the Other Options Are Less Suitable:

A. Use nested IF statements to set the colors by expression for each dimension value: While this would work, it would be unnecessarily complex to maintain and manage, especially with many dimension values.

B. Define the color values in the master measures and use the color library: This would only apply if the goal was to set colors based on measures, not dimensions. In this case, dimension consistency is required, not measure-based coloring.

D. Use the FieldIndex function to set the colors by expression for each dimension value: This would involve writing complex expressions that would not be as straightforward as using the built-in functionality of 'By Dimension' and 'Persistent colors'.

References for Qlik Sense Business Analyst:

Color Consistency Across Charts: The 'By Dimension' and 'Persistent colors' settings are recommended in Qlik Sense documentation when creating multi-chart layouts with shared dimensions, ensuring visual coherence across different charts.

ThePersistent colorsandBy Dimensionsettings offer a straightforward and maintainable way to create color associations across charts, making optionCthe verified solution.

In this scenario, the second measure (Count of MajorCities) is likely not being displayed because the two measures—Sum(Knowing sections)andCount(MajorCities)—are on vastly different scales. When two measures have significantly different ranges, one of them may not be visible on the same Y-axis, causing the issue you're seeing where no bars are visible for the second measure.

By converting the bar chart to acombo chart, the business analyst can display both measures with appropriate configurations. The combo chart allows you to display different measures in different ways, such as using one axis for the first measure (e.g., bars forSum(Knowing sections)) and another axis for the second measure (e.g., bars forCount(MajorCities)), ensuring that both are visible on the chart.

Key Concepts:

Combo Chart: This type of chart allows you to display multiple measures using different axis scales or types of visualization (e.g., bars and lines).

Scale Mismatch: When two measures differ significantly in scale, they may not be displayed properly on the same axis. A combo chart helps by allowing separate Y-axes for each measure.

Why the Other Options Are Less Suitable:

A. Enable Value labels: While value labels can help show specific data points, they won't resolve the issue of one measure being invisible due to scale differences.

B. Recreate as an alternative measure: This would allow switching between measures, but the requirement is to show both measures simultaneously.

C. Change Y-axis Range to Custom: While adjusting the Y-axis manually might help, it’s not the best solution because the scale difference between the two measures might still cause issues, and it would be harder to adjust dynamically.

References for Qlik Sense Business Analyst:

Combo Charts for Multiple Measures: Combo charts are recommended in Qlik Sense when you need to display multiple measures with different scales.

Thus, converting the bar chart to acombo chartensures both measures are properly displayed, makingDthe correct answer.

In the provided exhibit, the movie analyst filters by theLength Rangefield and notices a hyphen (“-”), which typically indicatesmissing datain Qlik Sense. When the analyst selects this hyphen, it filters out the rows where no data exists for the Length Range field.

Let’s review the options:

A. Six movies in the source data contain illegal characters for the Length Range field.This statement is incorrect. The hyphen (“-”) is not an indicator of illegal characters. In Qlik Sense, it usually representsnull values or missing data, not improperly formatted data.

B. Movies at the start of the 20th century often varied in length.This answer is not relevant to the specific observation of the hyphen in the Length Range field. The hyphen does not provide insights into the variation of movie lengths; it indicates missing data.

C. All movies from the 1920s or 1930s contain no data for Length Range.While the screenshot shows some movies from different decades, we cannot definitivelyconclude that all movies from a particular era are missing the Length Range data. The hyphen indicates that some movies across various years are missing data, but this does not apply to all movies from the 1920s or 1930s.

D. The source data for six movies is missing a Length Range.This is the correct interpretation. The hyphen in theLength Rangecolumn indicates that these six movies lack data for this field. Selecting the hyphen allows the analyst to identify movies with missing values in the Length Range field.

Key Qlik Sense Business Analyst References:

Hyphen (“-”) in Qlik Sensetypically represents null or missing values in a field.

Filter panesin Qlik Sense allow users to quickly see where data may be incomplete or missing, and selecting these null values provides immediate insight into which records are affected.

Thus, the correct determination is thatthe source data for six movies is missing a Length Range.

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 alookup tableis 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 optionBis the verified solution.

Aline chartis the most appropriate visualization for comparing two continuous measures (Profit and Revenue) over time. Line charts are designed to show trends and patterns over a continuous scale (such as time), making it ideal for this scenario where we need to observe how both Profit and Revenue vary across a period.

Key Concepts:

Continuous Scale: Line charts are specifically suited for continuous data like time, making them the preferred choice when tracking changes over time for multiple measures.

Dual Measure Comparison: A line chart allows you to plot two measures on the same axis, making it easy to compare their trends over the same period.

Why the Other Options Are Less Suitable:

B. Bullet chart: A bullet chart is used to compare a single measure against a target, not for tracking two measures over time.

C. Bar chart: Bar charts are better suited for comparing categorical data, not continuous measures over time.

D. Scatter plot: Scatter plots are used to compare relationships between two measures but are not suited for continuous time-based comparisons.

References for Qlik Sense Business Analyst:

Line Charts for Time Series Data: Line charts are the recommended visualization for comparing multiple measures over time in Qlik Sense, especially when working with continuous data like Profit and Revenue.

Thus, theline chartis the best choice for this scenario, makingAthe correct answer.

TheMulti KPIobject is designed to display multiple key measures in a compact and visually appealing format, making it ideal for a dashboard that requires a minimal number of visualizations but must present multiple key metrics. By usingmaster visualizations, the business analyst ensures consistency and reusability across different sheets. This setup also allows for easy navigation through the app, as users can drill down into more detailed sheets when needed.

Key Concepts:

Multi KPI: This visualization allows multiple key performance indicators (KPIs) to be displayed in a single object, reducing the need for multiple charts or visualizations while ensuring that critical metrics are visible.

Master Visualizations: These ensure that KPIs are consistent across the app and can be reused as needed, helping to maintain a clean and efficient dashboard.

Why the Other Options Are Less Suitable:

B. Dynamic text and image linked objects: This could work for navigation, but it wouldn’t meet the requirement of displaying multiple key measures in a minimal number of visualizations.

C. Bookmark: A bookmark is used to save a particular state of selections but isn’t useful for showing multiple KPIs simultaneously.

D. Container: While containers can hold multiple visualizations, the Multi KPI object is more suited to displaying multiple key measures in a compact space.

References for Qlik Sense Business Analyst:

Multi KPI for Compact Dashboards: Qlik Sense recommends using Multi KPI objects when there is a need to display multiple key metrics in a minimalistic format.

Thus,Ais the best choice to meet the CEO's requirements, making it the correct answer.

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, makingAthe correct choice.