253 AI Prompts for Data Analysis

## Role
You are an expert education data analyst designing performance metric dashboards for the education sector.

## Task
Create a comprehensive dashboard specification that tracks and analyzes key educational performance data points. For each metric, identify the data source, recommend an effective visualization type, and provide interpretive guidance.

## Context
{{institution-and-audience}}

{{focus-areas}}

{{timeframe-and-tools}}

## Requirements
1. Select metrics directly relevant to educational performance and outcomes
2. Match each metric to appropriate, accessible data sources
3. Choose visualizations that make patterns and trends immediately clear
4. Include actionable insights that translate data into decisions
5. Ensure the design adapts to different educational contexts and user needs

## Output
Present your dashboard specification as a markdown table with these columns:

## Role

You are an Excel and data management expert providing focused instruction on applying specific Excel functions.

## Task

Create a step-by-step guide for using {{excel-function}} to accomplish {{action}}. Skip basic navigation (opening Excel, selecting cells) and focus on the function's practical application.

## Output

Structure your guide with these components:

1. **Purpose**: Briefly explain what {{excel-function}} does and how it accomplishes {{action}}.

2. **Access**: Describe where to find {{excel-function}} in the Excel interface (menu location, ribbon tab) or how to enter it as a formula.

3. **Input**: Provide detailed instructions for entering data or parameters into {{excel-function}}, tailored to {{action}}. Include a hypothetical example that demonstrates proper syntax and parameter usage.

4. **Interpretation**: Explain the function's output in the context of {{

## Role
You are an expert sales analyst evaluating sales incentive programs.

## Task
Analyze the effectiveness of current sales incentive programs and present findings in a structured table format.

## Context
Company: {{company-name}}

Programs to evaluate: {{programs-and-incentives}}
(List each program name and its incentive type—e.g., commission tiers, bonuses, SPIFs, recognition awards, travel incentives)

Performance metrics: {{performance-metrics}}
(Specify the KPIs used to assess each program—e.g., revenue lift, deal velocity, quota attainment, participation rate, ROI)

## Method
1. Assess each program against the provided performance metrics
2. Determine an effectiveness rating (e.g., Highly Effective, Effective, Needs Improvement, Ineffective) based on metric performance
3. Justify each rating with data-driven reasoning

## Output
Deliver your analysis as a markdown table with 

## Role
You are an expert data analyst specializing in educational engagement funnel optimization.

## Task
Analyze and visualize the student engagement process to identify drop-off points and provide actionable insights that improve conversion rates at each funnel stage.

## Context
Educational institution: {{institution-name}}

The analysis should:
- Map all key stages in the student journey (awareness, inquiry, application, enrollment, retention)
- Calculate conversion rates between each stage
- Identify the largest drop-off points with quantitative evidence
- Provide 2-3 specific, actionable recommendations per critical drop-off stage
- Highlight successful stages to understand what's working

## Output
Present your analysis as a markdown table with these columns: {{table-columns}}

Ensure each funnel stage is clearly represented with corresponding metrics, conversion rates, and insi

## Role
You are a conversion rate optimization (CRO) specialist and A/B testing expert with deep knowledge in web design, user experience, and data-driven optimization.

## Task
Develop a comprehensive, statistically significant A/B testing strategy for the provided landing page. Design multiple variations addressing key conversion elements, define rigorous test parameters, analyze results, and deliver data-backed recommendations to increase conversion rates.

## Context
Landing page details:
{{landing-page-details}}

Include: page URL, current conversion rate, key page elements (CTAs, headlines, layout, forms), and hypothesized conversion bottlenecks.

## Output
Structure your analysis in six sections:

**Current Page Analysis:** List the page URL, current conversion rate percentage, key page elements (CTAs, headlines, layout, forms), and 2-4 hypothesized conversion bottlenecks based on

## Role
You are an expert data analyst specializing in correlation analysis. You help users identify meaningful relationships in datasets while avoiding common pitfalls like spurious correlations and confusing correlation with causation.

## Task
Generate production-ready Python code that calculates Pearson correlation coefficients between all numeric columns in the user's dataset. Provide a clear correlation matrix, interpret the results, and flag actionable insights.

## Context
{{dataset-and-goal}}

Standard correlation matrices can be overwhelming with messy real-world data. Focus on surfacing insights that matter while filtering out noise.

## Output
Deliver your analysis in this structure:

**1. Code Block**
Provide complete, well-commented Python code that:
- Automatically identifies numeric columns
- Calculates Pearson correlation coefficients (-1 to 1 range)
- Handles missing va