Qlik QSBA2024 - Qlik Sense Business Analyst Certification Exam-2024

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.

ANetwork chartis the most suitable visualization for representing processes and tasks that have dependencies, such as projects with co-dependent tasks and subtasks. The network chart allows you to visualize relationships between nodes (in this case, tasks and subtasks) and can display them in a structured manner with lines connecting them based on their relationships. The colors of the boxes (or nodes) can be determined by the status of each project or task, which matches the requirements.

Key Concepts:

Network Chart: It’s designed for showing interconnections or relationships between various elements. It is ideal when tasks or processes have dependencies or subtasks that need to be visually represented with links between them.

Color Representation: In a Network Chart, you can easily apply colors to nodes based on specific criteria, such as the status of the task, making it easier for users to track project progress at a glance.

Why the Other Options Are Less Suitable:

A. Sankey chart: While Sankey charts are used to show flow and relationships between categories, they are better suited for representing flows of data or values between stages, not hierarchical or task-related dependencies.

B. Grid chart: A grid chart is used to display values in a matrix but does not provide the relational and hierarchical representation needed for tasks and subtasks.

C. Org chart: Org charts are useful for showing hierarchies but are more structured for organization personnel or roles rather than co-dependent tasks and workflows.

References for Qlik Sense Business Analyst:

Network Diagram: Network charts are widely used for visualizing complex relationships between entities, which aligns with the need to visualize tasks and subtasks in project management.

Thus, aNetwork chartprovides the best solution for visualizing tasks and subtasks with their dependencies, makingDthe correct answer.

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.

To answer the two questions:

How many students are in the system?

What percentage of students have not yet attempted an exam?

The analyst needs to focus on theStudentIDfield, specifically in relation to theAttemptstable. This is because theAttemptstable captures all exam attempts made by students, and we can deduce which students have and have not made an attempt by examining the presence of StudentID values in this table.

Key Concepts:

Total Distinct Values: This provides the total number of unique students who have attempted exams. It helps identify how many students have made at least one attempt.

Subset Ratio: This compares the values ofStudentIDbetween theStudentstable and theAttemptstable. The subset ratio shows how many students in theStudentstable are represented in theAttemptstable. This ratio helps determine the percentage of students who have not yet attempted any exams.

Why the Other Options Are Less Suitable:

B. Non-null values and Subset ratio for the StudentID field in the Students table: Thenon-nullvalues in theStudentstable are not relevant to the question about exam attempts. The focus should be on whether theStudentIDis present in theAttemptstable.

C. Subset ratio and Present distinct values for the ExamID field in the Attempts table: This focuses on exams, not students. The question specifically relates to how many students have attempted exams.

D. Present distinct values and Density% for the ExamID field in the Exams table: This focuses on the number of exams and their density, which does not help in determining how many students have attempted or not attempted an exam.

References for Qlik Sense Business Analyst:

Subset Ratio and Distinct Counts: Qlik Sense’s data model viewer provides valuable metadata like thedistinct countof a field and itssubset ratiowhen compared to related fields in othertables. This is particularly useful for understanding relationships and gaps in the data, such as identifying students who have not yet made an exam attempt.

By focusing on theTotal distinct valuesandSubset ratiofor theStudentIDfield in theAttemptstable, the business analyst can easily determine the total number of students and the percentage who have not yet attempted an exam, makingAthe verified answer.

When users need to filter across many different fields and values in a Qlik Sense dashboard, the most efficient feature they can use isSmart Search. Smart Search allows users to quickly search across all fields within the data model, enabling them to find relevant information and apply filters in a streamlined manner.

A. Smart searchThis is the correct option.Smart Searchenables users to enter search terms and find matches across all fields in the data model, allowing for quick and intuitive filtering. It helps users locate specific data points or filter across multiple fields at once, making it highly efficient when multiple filter panes are needed.

B. Data model viewerThe Data Model Viewer provides a visual representation of the relationships between data tables in the model. While it's useful for understanding the data structure, it’s not a tool for filtering or user interaction with data.

C. Insight AdvisorThe Insight Advisor is designed for guided analytics, providing suggestions and generating visualizations based on user queries. It does not offer the comprehensive filtering capabilities that Smart Search does.

D. Governed self-serviceGoverned self-service refers to the balance between providing users with flexibility in creating their own visualizations while maintaining control over data governance. It’s not related to filtering or searching data in the same way as Smart Search.

Key Qlik Sense Business Analyst References:

Smart Searchin Qlik Sense is designed to provide fast, interactive search capabilities that span across all fields, enabling complex filtering in an easy-to-use interface.

This feature allows users to filter multiple fields simultaneously, saving time and effort when analyzing diverse data sets.

Thus, the correct feature for filtering on multiple values across different fields isSmart Search.