Dataset Summary and Insights
Paste or describe a dataset and get an instant summary of key statistics, patterns, anomalies, and actionable insights.
Prompt Template
You are a senior data analyst. Analyze the following dataset and provide a comprehensive summary: Dataset description: [what the data is about] Source: [where it came from] Time period: [date range] Key columns: [list column names and types] Business question: [what we're trying to answer] [PASTE SAMPLE DATA OR DESCRIBE IT HERE] Provide: 1. Dataset overview (rows, columns, data quality notes) 2. Key statistics for numeric columns (mean, median, range, outliers) 3. Top 5 findings / patterns 4. Anomalies or data quality issues 5. 3 actionable recommendations based on the data 6. Suggested next analyses to run
Example Output
Dataset Analysis: E-commerce Sales Q1 2026
**Overview:** 12,450 rows × 8 columns. Data appears clean with 0.3% null values in 'discount_applied' column (acceptable).
Key Statistics
| Metric | Value |
|--------|-------|
| Total Revenue | $2.4M |
| Avg Order Value | $192 |
| Median Order Value | $134 (right-skewed — a few large orders pull mean up) |
| Highest Revenue Category | Electronics (38%) |
| Return Rate | 11.2% |
Top 5 Findings
1. **Weekend orders have 23% higher AOV** than weekday orders
2. **February dip:** Revenue dropped 31% in week 2 — correlates with shipping delay incident
3. **Mobile conversion** (2.1%) is half of desktop (4.3%) — UX opportunity
4. **Repeat customers** (28% of base) generate 61% of revenue
5. **Returns highest in Clothing** (18.4%) — sizing issue likely
Recommendations
1. Investigate and fix mobile checkout friction (potential +$240K/quarter)
2. Launch retention campaign targeting the 72% of customers who've only ordered once
3. Review clothing size guides and add size charts to reduce returns
Tips for Best Results
- 💡Paste a 10-20 row sample with column headers — even a small sample enables much better analysis than a description alone
- 💡Always state the business question upfront — the same data yields different insights depending on what you're trying to decide
- 💡Ask for a 'data quality scorecard' separately if your dataset is large — issues like nulls and duplicates need their own audit
Frequently Asked Questions
What is the Dataset Summary and Insights prompt?
Paste or describe a dataset and get an instant summary of key statistics, patterns, anomalies, and actionable insights. It's a free ChatGPT prompt template from our Data Analysis collection — copy it, fill in the bracketed variables, and paste it into your AI tool.
Which AI tools work with this prompt?
It's written and tested for ChatGPT, Claude and Gemini. Any AI assistant that accepts free-form text prompts will handle it well.
How do I customize this ChatGPT prompt?
Replace the bracketed variables — such as [what the data is about], [where it came from], [date range] — with your own details before running it. Paste a 10-20 row sample with column headers — even a small sample enables much better analysis than a description alone
Is this prompt free to use?
Yes. Every prompt on PromptAtlas is free to copy, customize, and use — no signup required.
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