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Qlik Sense Business Analyst Certification Exam - 2024 Sample Questions (Q12-Q17):

NEW QUESTION # 12
An app needs to load a few hundred rows of data from a .csv text file. The file is the result of a concatenated data dump by multiple divisions across several countries. These divisions use different internal systems and processes, which causes country names to appear differently. For example, the United States of America appears in several places as 'USA', 'U.S.A.', or 'US'.
For the country dimension to work properly in the app, the naming of countries must be standardized in the data model.
Which action should the business analyst complete to address this issue?

A. Cleanse the source text file prior to loading
B. Load a lookup table to convert values
C. Create a calculated master dimension expression
D. Use the Replace option in Data manager

Answer: B

Explanation:
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 a lookup table is 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 option B is the verified solution.

NEW QUESTION # 13
A business analyst receives an image of a dashboard from the HR Director and is asked to recreate the image in Qlik Sense. The image shows charts for:
* Company employee structure
* Average employee salary by region
* Geographical representation of office capacity
* Company retention over time
Which charts will meet these analysis requirements?

A. Map chart, org chart, line chart, bar chart
B. Line chart, network chart, bar chart, map chart
C. Line chart, sankey chart, map chart, bar chart
D. Map chart, grid chart, line chart, KPI chart

Answer: A

Explanation:
To recreate the dashboard image provided by the HR Director, the following charts are needed:
Map chart: To show the geographical representation of office capacity.
Org chart: To show the company employee structure.
Line chart: To show company retention over time.
Bar chart: To show average employee salary by region.
Key Concepts:
Map Chart: Used to visualize geographical data, such as office capacity across different locations.
Org Chart: Ideal for displaying hierarchical structures, such as the employee structure of a company.
Line Chart: Best suited for showing trends over time, such as employee retention.
Bar Chart: A good choice for comparing salaries across regions.
Why the Other Options Are Less Suitable:
A . Sankey chart: This chart is used for flow or process analysis, not employee structure.
B . Network chart: Network charts show relationships but are not ideal for hierarchical structures like an org chart.
C . Grid chart and KPI chart: These charts are not well-suited for the types of data required in this scenario.
References for Qlik Sense Business Analyst:
Chart Selection for HR Dashboards: Qlik Sense provides various visualization options, and selecting the correct chart for each type of data is essential for accurate and clear representation.
Thus, the correct combination of charts is D-Map chart, org chart, line chart, and bar chart-making it the verified answer.

NEW QUESTION # 14
The sales manager is investigating the relationship between Sales and Margin to determine if this relationship is linear when choosing the dimension Customer or Product Category.
The sales manager wants to have the potential percentage Sales for each Stage (Initial to Won) of the sales process.
Which visualizations will meet these requirements?

A. Combo chart: Measures Sales and Margin, Dimensions Customer or Product category Pie chart: Dimension Stage, Measure Sales
B. Distribution plot: Alternative measures Sales and Margin, Alternatives dimensions Customer or Product category Bar chart: Dimension Stage, Measure Sales
C. Scatter plot: Measures X-axis Sales and Y-axis Margin, Dimensions Customer or Product category Bar chart: Dimension Stage, Measure Sales
D. Scatter plot: Measures X-axis Sales and Y-axis Margin, Alternative dimensions Customer or Product category Funnel chart: Segments Stage, Width Sales

Answer: D

Explanation:
For analyzing the relationship between Sales and Margin, a scatter plot is ideal, as it allows you to visualize the relationship between two measures (Sales and Margin) across various dimensions such as Customer or Product Category. The funnel chart is perfect for visualizing stages in a sales process, as it shows how sales progress from the initial stage to the final (Won) stage, with the width of each segment representing the total sales for each stage.
Key Concepts:
Scatter Plot: This type of chart is specifically designed to visualize the correlation or relationship between two measures, making it ideal for analyzing Sales versus Margin across different dimensions.
Funnel Chart: This chart is particularly suited for visualizing the sales stages, as it visually demonstrates the proportion of sales moving through each stage of the sales funnel.
Why the Other Options Are Less Suitable:
A . Scatter plot and Bar chart: While a scatter plot is correct for analyzing Sales and Margin, a bar chart won't adequately represent the different stages of the sales process as effectively as a funnel chart.
C . Combo chart and Pie chart: A combo chart could potentially work, but it would not show the relationship between Sales and Margin as clearly as a scatter plot. A pie chart is also less effective for representing stages in a sales funnel.
D . Distribution plot and Bar chart: A distribution plot does not effectively show the relationship between two measures, and a bar chart isn't the best choice for visualizing the stages of a sales process.
References for Qlik Sense Business Analyst:
Scatter Plot for Relationships: This chart type is highly recommended when exploring relationships between two continuous variables, such as Sales and Margin.
Funnel Charts: These are ideal for visualizing how data moves through various stages of a process, such as sales stages, from initial engagement to final sale.
Therefore, the combination of a scatter plot and a funnel chart provides the best solution, making B the correct answer.

NEW QUESTION # 15
A business analyst is creating an app using a dataset from ServiceNow. The dataset shows information about support cases, including how many days it has been since the case was opened (age).
The app requirements are:
* The dashboard must display support cases in categories based on the age (New, Aging, and Beyond Service Level Agreement)
* The categories will be used multiple times in the dashboard
* Given the volume of support cases, it is expected that the dataset will grow to be very large Which solution is the most efficient way for the business analyst to create this app?

A. Write a master dimension with a nested IF statement to group ages together
B. Ask the ServiceNow team to create the field in the source dataset
C. Create a new field for the categories using the Bucket option in the Data manager
D. Create an Excel sheet with all possible age values and the corresponding categories to add to the data model

Answer: C

Explanation:
To efficiently categorize support cases based on age (New, Aging, Beyond SLA) for use in multiple places across the dashboard, the Bucket option in the Data Manager is the most efficient approach. Bucketing allows the business analyst to create new categories based on the values in an existing field (in this case, the age of support cases). Since the dataset is expected to grow, creating the categories directly within Qlik Sense ensures that the process is scalable without the need for external tools or extensive coding.
Key Concepts:
Bucket Function: This allows you to group numeric fields into predefined ranges or categories. The function is highly scalable, making it suitable for large datasets.
Efficiency: Creating a new field using Bucketing ensures that the categorization is done directly in the app, avoiding the need for external data sources or nested IF statements, which could impact performance.
Why the Other Options Are Less Suitable:
A . Ask the ServiceNow team to create the field: This would create a dependency on external teams and could delay the development process.
B . Create an Excel sheet: This adds unnecessary complexity and isn't scalable as the dataset grows.
D . Write a master dimension with a nested IF statement: While this could work, it's less efficient for handling large datasets and could result in slower performance.
References for Qlik Sense Business Analyst:
Bucketing Data: Qlik Sense recommends using the Bucketing feature for creating predefined ranges or categories, especially when dealing with large datasets.
Thus, using the Bucket option to create a new field for categories is the most efficient solution, making C the correct answer.

NEW QUESTION # 16
A business analyst needs to build a chart that enables users to analyze the correlation between the following measures for all products:
* Product Sales ($)
* Order Volume
* Margin%
Which visualization should the business analyst use?

A. Pivot table
B. Combo chart
C. Scatter plot
D. Multi KPI

Answer: C

Explanation:
A scatter plot is the most appropriate visualization for analyzing the correlation between Product Sales ($), Order Volume, and Margin %. Scatter plots are ideal for showing relationships between two or more continuous variables, which is crucial for identifying trends or correlations among these measures.
Key Concepts:
Scatter Plot: This chart type is specifically designed to display correlations between measures, making it the ideal choice for visualizing relationships between Product Sales, Order Volume, and Margin %.
Multiple Measures: Scatter plots in Qlik Sense can plot two measures on the X and Y axes and can use colors or bubbles to represent additional measures (such as Margin %).
Why the Other Options Are Less Suitable:
A . Multi KPI: A Multi KPI displays multiple metrics but doesn't show correlations between them.
B . Combo chart: A combo chart combines bar and line charts but is not suited for analyzing correlations between multiple continuous measures.
D . Pivot table: While useful for data aggregation, a pivot table does not provide a clear visualization of correlations between measures.
References for Qlik Sense Business Analyst:
Scatter Plot for Correlation Analysis: Scatter plots are recommended in Qlik Sense when exploring relationships between multiple continuous variables.
Thus, the scatter plot is the most effective visualization for analyzing the correlation between Product Sales, Order Volume, and Margin %, making C the correct answer.

NEW QUESTION # 17
......

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