Exactprep QSBA2024 Questions

In this case, we need to count how many unique rodents have made at least one attempt at any maze. Since the relationship between the Rodent table and the MazeEscapes table is a one-to-many relationship (each rodent may attempt several mazes), the best approach is to base the calculation on theMazeEscapestable, as it holds the actual records of rodent attempts.

By creating a new fieldRodentID_Counterin theMazeEscapestable, the analyst ensures that each rodent’s attempt is captured. Using theCount (Distinct RodentID_Counter)as the KPI expression then accurately counts each unique rodent that has made at least one attempt, without counting multiple attempts by the same rodent.

Key Concepts:

Distinct Count: The distinct count ensures that rodents who have made multiple maze attempts are only counted once.

MazeEscapes Table: This table holds the records of each attempt, making it the correct source for this KPI.

Why the Other Options Are Less Suitable:

B. Sum (RodentID_Counter) in the Rodent table: This would incorrectly sum the number of rodents rather than counting unique attempts, leading to inaccurate results.

C. Sum (RodentID_Counter) in the MazeEscapes table: Summing the counter would not account for the distinct rodents, leading to incorrect counting.

D. RodentID_Counter in the Rodent table: This would not correctly reflect the rodents that have made an attempt, as not every rodent in the Rodent table may have attempted a maze.

References for Qlik Sense Business Analyst:

Distinct Count in KPI: It is best practice to use Count(Distinct ...) when working with KPIs that require unique counts, such as counting distinct rodents in this scenario.

Thus,Ais the verified answer because it ensures that each rodent is counted once, based on their attempts in the MazeEscapes table.

When working with Qlik Sense apps, a business analyst often encounters situations where visualizations may be highly similar between different apps, even if the underlying data models differ. In such cases, efficiency is crucial, and Qlik Sense provides several methods to reuse visualizations across apps. Let's break down the options:

A. Add the base visualization to the master items and use it as a template for the new visualization.This option suggests adding the base visualization to the master items. While master items are useful for reusing dimensions, measures, and visualizationswithin the same app, they do not easily transfer across apps. In this case, since the visualization is required in a different app, this approach would not be the most efficient or feasible.

B. Note the properties of the base visualization and create the new visualization from scratch.This option involves manually noting the properties and then replicating them in the new app. While this would work, it is labor-intensive and increases the likelihood of human error, especially in complex visualizations. It is not an efficient solution for business analysts looking to save time.

C. Copy and paste the visualization between the apps, and update the data properties in the new app.This is the most efficient solution. Qlik Sense allows for thecopying and pasting of visualizations between different apps, and you can then adjust the properties to fit the new data model. This option enables the business analyst to leverage existing visual work without having to recreate it from scratch. Updating the data properties, such as dimensions and measures, ensures that the visualization functions correctly with the new data model.

D. Open both apps at the same time. Drag the base visualization between apps, then update the data properties.While this seems like a practical option, Qlik Sense does not allow users to drag and drop visualizations directly between different apps. As a result, this method is not possible.

Key Qlik Sense Business Analyst References:

Copying and pasting visualizationsis a common practice in Qlik Sense when working between different apps. The ability to quickly replicate and adapt visualizations across apps helps streamline the development process.

Adjustingdata propertiessuch as dimensions and measures ensures that visualizations adapt to different data models without the need for full recreation.

Efficiency and error reduction are critical in app development, andcopy-paste functionalitiesare specifically designed to reduce manual work in such scenarios.

In conclusion, the correct and most efficient action for the business analyst to take isC, copy and paste the visualization, and then update the relevant data properties.

TheDensityvalue in the Data Model Viewer provides a measure of how "dense" or "sparse" a field is in terms of data completeness. A higher density value means fewer nulls, while a lower value indicates more nulls. By checking the density value for each field, the business analyst can determine the percentage of non-null values, which is critical for understanding data quality and completeness.

Key Concepts:

Density Value: This is a measure in Qlik Sense that indicates the proportion of non-null values in a field. A field with a high density is mostly populated, while a lower density indicates a high proportion of null values.

Data Model Viewer: This tool allows analysts to inspect the structure and quality of data fields, including metrics such as density.

Why the Other Options Are Less Suitable:

B. Preview Panel: While the Preview Panel shows sample data, it does not provide a comprehensive measure of null values and is more suited for a quick glance rather than detailed analysis.

C. Tags fields with $null: This would show if the field contains any nulls, but it wouldn’t quantify the level of nulls.

D. Subset Ratio: The subset ratio compares values across related tables, not null values within individual fields.

References for Qlik Sense Business Analyst:

Data Quality in Qlik Sense: Using theDensityvalue is the best way to assess the proportion of null values in a field, making it ideal for the business analyst to understand the completeness of the data.

Thus,Ais the correct answer because the density value provides the required insight into the level of nulls in each field.

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 isD—Map chart, org chart, line chart, and bar chart—making it the verified answer.