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CSV Data Analysis Report Generator

Added Apr 1, 2026

You are a senior data analyst. I will provide you with a dataset about [DATASET_DESCRIPTION]. Analyze the data and produce a comprehensive report that includes: 1) Executive Summary with 3-5 key findings, 2) Data Quality Assessment noting missing values, outliers, and anomalies, 3) Descriptive Statistics for all numerical columns, 4) [ANALYSIS_TYPE] analysis with visualizations described in detail, 5) Trend identification and pattern recognition, 6) Correlation analysis between [KEY_VARIABLES], 7) Actionable recommendations based on the findings, and 8) Suggested next steps for deeper analysis. Present findings using clear headers, bullet points, and reference specific data points to support each conclusion.

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About This Prompt

Turning raw data into actionable insights is where most analysis efforts stall. This prompt provides a structured analytical framework that ensures no important dimension of your data goes unexplored. From basic data quality checks to advanced correlation analysis, it guides the AI through a systematic investigation that mirrors how experienced analysts approach a new dataset. The inclusion of actionable recommendations transforms the output from a passive report into a strategic decision-making tool. Ideal for business analysts, product managers, and founders who need to extract meaning from their data quickly.

Variables to Customize


[DATASET_DESCRIPTION]

What the data contains

Example: e-commerce sales transactions from January to December 2025


[ANALYSIS_TYPE]

Primary type of analysis needed

Example: time-series and seasonal decomposition


[KEY_VARIABLES]

Variables to analyze relationships between

Example: customer acquisition cost, lifetime value, and churn rate

Tips for Best Results

Paste a sample of your actual data headers and first few rows for more specific analysis
Specify your business context so recommendations are actionable for your situation
Ask for Python or R code snippets to reproduce the analysis on your full dataset

Example Output

## Executive Summary

1. Revenue peaked in Q4 with a 34% increase over Q3, driven primarily by the holiday promotional campaign launched November 15.
2. Customer acquisition cost (CAC) increased 22% year-over-year while lifetime value (LTV) decreased 8%, creating a concerning LTV:CAC ratio decline from 3.2 to 2.4.
3. Mobile transactions now represent 67% of all orders, up from 51% in the prior year.
4. Three product categories account for 78% of total revenue...

data-analysis reporting statistics business-intelligence