Audit beginner Works with: Any AI

Power BI Visual Choice and Misleading Chart Audit

Table output

Review the charts on a Power BI page for misleading scales, poor chart types and clutter, and suggest clearer visuals matched to each question.

The Open buttons send the prompt text as currently shown below to that site only when you click. Fill in the placeholders first.

[VERIFY] is an editorial flag, not a blank to fill. Wherever the prompt shows [VERIFY], check that item against a reliable source before you use it.

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Please critique the visuals on one Power BI report page for clarity and honesty. I will describe each visual. Mark statements about specific Power BI visual options or formatting menus [VERIFY].

Inputs: for each visual, the type, the fields used, the axis ranges, colours, and the title [VISUAL_DETAILS], the question each is meant to answer [VISUAL_QUESTIONS], the audience [AUDIENCE], and where it will be viewed, such as a meeting screen or a phone [VIEWING_CONTEXT].

Return: (1) a table with columns Visual, Question it answers, Current type, Suitable? (Yes / Partly / No), Problem, Better option, Reason; (2) check each for misleading elements: truncated axes on bar charts, dual axes without labels, pie charts with too many slices, 3D effects, inconsistent colours for the same category across visuals, missing units, unlabeled totals, sorting that hides ranking; (3) a count of problems by type, and the number of visuals on the page against a suggested limit of [MAX_VISUALS]; (4) accessibility notes: contrast, colour-only meaning, text size, alt text; (5) a redesigned page outline as a list with the order of visuals and one-line titles that state the finding rather than the topic; (6) five-line checklist for any new page.

Guardrails: do not invent data or insights; if I gave no data, say what cannot be judged. Don't impose one style as the only right way. Keep recommendations realistic for a non-designer.

Add a worked example with invented details: a bar chart of sales with the axis starting at 90 and values 92 and 98. Show how the visual differences exaggerate a 6.5 percent change (6 / 92).

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