Prompting for Data Analysis
Using AI to interpret data, generate insights, write SQL queries, and create charts.
Data Insight Mode
Input raw CSV or table data and ask: 'What are the three most surprising trends?'
AI is a powerful data analyst when paired with the right prompts. Whether you have a CSV, a database schema, or raw numbers, AI can help you write SQL queries, interpret trends, create Python data scripts, and even summarize findings in plain language for non-technical stakeholders.
Data Analysis Prompt Templates
SQL Query: You are a SQL expert. Given the table schema: [paste schema], write a query that [describe what you need]. Optimize for performance.
CSV Analysis: Analyze the following data and identify the top 3 trends: [paste data or describe columns]. Present findings as bullet points.
Python Chart: Write a Python script using matplotlib/pandas that reads 'sales.csv' and plots a bar chart of monthly revenue. Add axis labels and a title.
Plain English Summary: Summarize the following data in 3 sentences for a non-technical manager: [paste data].
Example: Prompt for a Data Summary
How to ask AI to analyze a dataset and produce a readable report:
You are a senior data analyst.
I have a dataset with these columns: Date, Product, Region, UnitsSold, Revenue.
Analyze the following monthly sales data and:
1. Identify the top 3 performing products by revenue
2. Identify the lowest performing region
3. Calculate month-over-month growth %
4. Suggest 2 actionable improvements based on the data
[paste your data here]
Present results in a clean, structured format with clear headings.Paste Small Data Samples
AI context windows can't handle massive datasets. Instead, paste 10-20 representative rows and tell the AI the total size of your dataset. For large data, use AI to write the analysis code (Python/SQL) that you then run yourself.