Identify Patterns and Trends PL-300 Practice Questions (Page 5)

Questions 21–25

1. 21foundation · easy

   In Power BI Desktop, what is the purpose of the Grouping feature for data fields?

   • ATo combine multiple related items into a single category for analysis
   • BTo split a single column into multiple columns based on a delimiter
   • CTo create a calculated measure that aggregates values from multiple tables
   • DTo change the data type of a column from text to numeric
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2. 22expert · hard

   A network analyst is monitoring daily bandwidth usage. The analyst wants to automatically detect days with unusually high or low usage, but also wants to forecast next week's usage to plan capacity. The analyst has noticed that the Anomaly Detection feature flags too many days as anomalies because of weekly seasonality. What should the analyst do to reduce false positives while still getting a forecast?

   • AUse the Analyze feature to explain each anomaly and manually decide which to ignore.
   • BRemove the seasonality by aggregating the data to a weekly level before applying anomaly detection.
   • CAdd a reference line at the average usage and consider anything above it an anomaly.
   • DAdjust the sensitivity of the Anomaly Detection feature and enable forecasting on the same chart.
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4. 23foundation · easy

   What is the purpose of the Decomposition tree visual in Power BI?

   • ATo compare actual values against a target using a bullet chart
   • BTo display hierarchical data in a tree-like structure for navigation
   • CTo break down a measure across multiple dimensions to analyze the contributing factors
   • DTo create a forecast of future values based on historical data
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5. 24application · medium

   A retail analyst has a sales table with a 'Product Name' column containing hundreds of individual product names. The analyst wants to create a visual that shows sales performance for broad product categories (e.g., 'Electronics', 'Clothing') without modifying the underlying data model. The analyst also wants to add a line showing the average sales across all categories for comparison. What should the analyst do?

   • ACreate a calculated column that maps each product name to a category, then use that column in the visual and add an average line.
   • BUse the Analyze feature to automatically group products and add a trend line.
   • CUse the Grouping feature on the 'Product Name' field to create groups, then add an average line to the visual.
   • DCreate a new table with category mappings and relate it to the sales table, then add a constant line for the average.
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6. 25application · medium

   A data analyst is reviewing a dataset of customer ages and notices a few customers with ages over 100, which are likely data entry errors. The analyst wants to identify these unusual values and then decide whether to exclude them from the analysis. What should the analyst do?

   • AUse the Analyze feature to explain why the average age is high.
   • BAdd error bars to a bar chart of average age by customer segment.
   • CCreate a histogram with age bins to visually spot the isolated bars at the high end.
   • DUse the Anomaly Detection feature on a line chart of age over time.
   Reveal Solution Discussion Select an answer first