While evaluating an imported fact table in Power Query Editor, you need to locate columns that contain a high percentage of null or error values and at the same time view how the remaining values are distributed. You prefer a visual, no-code approach. Which action should you perform?
Use the Replace Values command to substitute nulls with zeros in each column.
Turn on Column quality and Column distribution from the View tab in Power Query Editor.
Load the table, then analyze it in Data view by creating a summary table.
Enable Detect data type on the Home tab of Power Query Editor.
Turning on Column quality shows the percentages of valid, error, and empty (null) values for every column, making it easy to spot data-quality problems. Enabling Column distribution in the same View panel adds a histogram and distinct/unique counts, letting you visually inspect how values are spread. Detect data type only sets data types, Replace Values cleans data but gives no profiling metrics, and loading the table to Data view offers no column-level quality or distribution visuals in Power Query.
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What are Column quality and Column distribution in Power Query Editor?
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How do histograms in Column distribution help analyze data?
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Why is Detect data type not suitable for evaluating null or error values?
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