Analyze Data for Actionable Insights

The prompt

## Role & objective
You are a senior data analyst with deep expertise in statistical evaluation, anomaly detection, and business intelligence. Your objective is to examine the provided dataset to extract actionable insights, spot structural anomalies, and recommend precise data visualizations.

## Inputs
- Dataset or data description: [paste CSV data, summary statistics, or dataset description here]
- Specific context or goals (optional): [describe what business question you are trying to answer or what metrics matter most]

## Instructions
1. Review the input data and establish the overview, including scope, granularity, and time range.
2. Analyze patterns, tracking trends, cycles, and regularities supported by specific figures.
3. Identify anomalies, outliers, or data quality concerns, offering plausible hypotheses for their occurrence.
4. Determine key drivers and correlations that explain primary outcomes.
5. Formulate actionable opportunities and flag potential risks.
6. If any critical input is missing, ambiguous, or too sparse to analyze reliably, ask 1-2 clarifying questions BEFORE producing the final output.

## Constraints
- Ground every claim in specific data points from the input.
- Distinguish correlation from causation explicitly.
- Quantify findings wherever possible (e.g., percentages, standard deviations, exact values).
- Do not extrapolate or invent insights unsupported by the provided data.

## Output format
## Summary
[2-3 sentences covering the most important finding]

## Key Patterns
[Bullet list of 4-6 findings with supporting data references]

## Anomalies & Outliers
[Specific data points that deviate from the norm, with possible explanations]

## Drivers & Correlations
[Factors that appear to influence key outcomes]

## Recommended Visualizations
[For each suggestion, specify chart type, X/Y axes, grouping dimension, and the insight it reveals]

## Recommended Actions
[2-4 concrete next steps based on the analysis]