QSBA2024 Exam Dumps : Qlik Sense Business Analyst Certification Exam-2024

When loading data from an Excel file with more than 100 columns, where only columns with the suffix _c are relevant, the most efficient approach is to use theData Manager. The Data Manager provides a preview of the table being loaded, allowing the business analyst todeselect columnsthat do not have the _c suffix. This is a quick and straightforward method that avoids manual editing of the Excel file and allows the analyst to focus on the necessary columns.

Key Concepts:

Data Manager Preview: The Data Manager allows you to inspect and modify which columns will be loaded into the data model. The preview panel makes it easy to deselect columns that are not needed.

Efficient Data Loading: By using the Data Manager, the business analyst can avoid loading unnecessary columns, ensuring a cleaner and more manageable data model.

Why the Other Options Are Less Suitable:

A. Load all columns: This would load unnecessary columns, leading to a bloated data model with duplicates and irrelevant data.

B. Utilize filter functionality: While filtering could work, deselecting fields directly in the preview is more efficient and straightforward.

C. Edit the Excel file: Manually editing the Excel file is unnecessary and could lead to errors, especially when Qlik Sense provides tools to handle this within the platform.

References for Qlik Sense Business Analyst:

Data Manager for Field Selection: Qlik Sense recommends using the Data Manager to inspect and selectively load data fields, which is particularly useful when dealing with large datasets.

Thus,Dis the best solution because it allows for selective loading of relevant columns, making it the 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.

The banking dashboard requires several KPIs and visualizations based on current year (CY) and last year (LY) revenue, as well as cost and customer satisfaction. To build the required measures, the fieldsCY Revenue, LY Revenue, and CY Costare necessary because they provide the comparison between the current and previous year, as well as cost-related data for the specific calculations.

Key Concepts:

KPI for CY vs LY Revenue: This requires both CY Revenue and LY Revenue fields.

Scatter Plot for Cost vs Revenue: This comparison requires both CY Revenue and CY Cost to create the necessary relationship in the scatter plot.

Treemap for Customer Satisfaction: In addition to the customer satisfaction rating, the field CY Revenue would likely be used for additional insights by region.

Table with CY Cost: The table requires CY Cost data along with other relevant fields like record number, financial instrument, and bank.

Why the Other Options Are Less Suitable:

B. CY Revenue, LY Revenue, Cost: While this covers the revenue fields, it does not specifically includeCY Cost, which is needed for the table and scatter plot.

C. Revenue and Cost: This option is too general and does not distinguish between current year and last year revenue, which is essential for the KPI.

D. Revenue and CY Cost: This does not include LY Revenue, which is required for the KPI.

References for Qlik Sense Business Analyst:

Comparison Measures in Qlik Sense: In Qlik Sense, comparisons across time periods like CY and LY require specific fields to calculate accurate insights, and it’s essential to ensure the appropriate fields are included for each visualization.

Thus,Aprovides the correct set of fields for the required dashboard, making it the verified answer.