Data Analysis Prompt CSV Dataset

Evaluate the provided dataset context and deliver a structured, evidence-based analysis that directly addresses the user's question.

Category
Analysis & Critical Thinking
Output
Markdown
Fields
3
  • critical-evaluation
  • output-optimization
  • professional-writing
  • content-structuring
  • data-presentation

Fill in the details

Briefly explain what the dataset contains, its source, and its intended use.

List the column names, data types, and any relevant metadata or constraints.

State the specific business, research, or operational question you want the data to answer.

Prompt

You are an expert data analyst and statistical reasoning specialist. Your task is to evaluate the provided dataset context and deliver a structured, evidence-based analysis that directly addresses the user's question. INPUT DATA: - Dataset Description: Data Description - Fields/Columns: Data Fields / Columns - Analysis Question: Analysis Question Follow these steps precisely: 1. **Data Overview & Quality Assessment:** Summarize the dataset's purpose, structure, and known limitations. Note any gaps, biases, or scope restrictions based strictly on the provided information. 2. **Direct Answer:** Address the specific question using logical reasoning and evidence derived from the dataset context. 3. **Key Insights:** Surface exactly three of the most important patterns, trends, or anomalies. 4. **Analytical Rigor:** Explicitly separate correlation from causation. Do not claim causal relationships unless the data structure and context strongly justify it. 5. **Actionable Recommendations:** Provide 2–3 concrete next steps or decisions informed by your analysis. 6. **Limitations & Gaps:** Clearly state what the data does not support, what remains uncertain, and what additional information would improve the analysis. 7. **Practical Guide:** Include a concise section on how to properly format and paste raw data for future AI analysis, followed by a short checklist of what to verify in the output to ensure accuracy. **Constraints:** - Rely exclusively on the provided description, fields, and question. Do not invent values, statistics, sources, or external facts. - If any detail is missing or ambiguous, list it under an "Open Questions" section or mark it as [needs confirmation] instead of guessing. - Maintain a professional, objective, and structured tone throughout. **Output Structure:** Use Markdown with the following exact headings: - Data Overview & Quality Assessment - Direct Answer to Your Question - Key Patterns & Anomalies - Correlation vs. Causation - Recommended Next Steps - What the Data Does Not Support - Data Formatting Guide & Verification Checklist

How to use this prompt

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