Data analysis with AI requires precise prompts that specify data format, analysis type, and desired output. These templates help extract meaningful insights from datasets.
Data Summary Prompts
Request statistical overviews. “Analyze this sales dataset with 10,000 rows. Provide mean, median, mode, standard deviation for revenue column. Identify outliers and trends.”
Visualization Requests
Specify chart types. “Create a visualization strategy for customer age distribution data. Recommend appropriate chart types and explain reasoning for each suggestion.”
Trend Identification
Find patterns in data. “Analyze monthly revenue data from 2020-2025. Identify seasonal patterns, growth trends, and anomalies. Highlight significant changes.”
Comparative Analysis
Compare datasets. “Compare Q1 vs Q4 performance metrics across five product categories. Calculate percentage changes and identify best performers.”
Predictive Modeling
Forecast future values. “Based on historical sales data, predict next quarter revenue. Explain methodology and confidence intervals.”
Correlation Analysis
Find relationships. “Analyze correlation between marketing spend and customer acquisition. Identify strong correlations and causal relationships.”
Leave a Reply