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Data Analysis Prompts

Master advanced data analysis and statistical interpretation with proven frameworks. Transform raw data into actionable insights using structured methodologies.

Data Interpretation

Analyze complex datasets and extract meaningful insights using statistical methods

Visualization Design

Create effective data visualizations that communicate insights clearly

Statistical Analysis

Perform rigorous statistical analysis with proper hypothesis testing

3 Expert Prompts
Data Scientists, Analysts, Researchers, Business Intelligence
Advanced Level

Ready to analyze data and generate insights? Start with any prompt below to get structured, professional data analysis guidance.

COSTAR Prompt Engineering Framework

All prompts in this collection use the COSTAR framework for optimal results. This structured approach ensures clear, effective communication with AI tools.

Context

Set the scene and establish your role or expertise level. This helps the AI understand your perspective and capabilities.

Objective

Clearly state what you want to achieve. Be specific about the desired outcome and any constraints.

Style

Define the tone, voice, and format you want. This ensures consistency with your brand and audience.

Task

Break down the specific actions or steps required. Provide clear instructions and structure.

Audience

Identify who the content is for. Understanding your audience helps tailor the message appropriately.

Response

Specify the format and structure you want in the response. This ensures you get exactly what you need.

Creating Great Prompts: A Quick Guide

Learn the key principles that separate effective prompts from ineffective ones, and how to craft prompts that deliver exceptional results.

What Great Prompts Do

  • Provide Clear Context: Set the scene and establish expertise level
  • Define Specific Objectives: State exactly what you want to achieve
  • Include Relevant Constraints: Specify format, tone, and limitations
  • Give Clear Instructions: Break down complex tasks into steps
  • Consider the Audience: Tailor content for specific readers
  • Request Structured Output: Specify desired format and organization

What Poor Prompts Do

  • Lack Specificity: Vague requests produce generic results
  • Ignore Context: No background leads to irrelevant responses
  • Skip Constraints: Missing boundaries create unfocused output
  • Assume Understanding: Unclear instructions cause confusion
  • Forget the Audience: Generic content misses the mark
  • Accept Any Format: Unstructured responses are hard to use

Pro Tips for Success

  • Start with Context: "You are an expert in..." sets the right tone
  • Be Specific: Include numbers, examples, and clear parameters
  • Use Examples: Show the AI what you want with sample outputs
  • Iterate and Refine: Test and improve your prompts over time
  • Consider Constraints: Set boundaries for better focus
  • Request Structure: Ask for organized, actionable responses

Data Analysis Prompts

Ready-to-use prompts for comprehensive data analysis and insights generation

Customize Your Prompts

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Data Interpretation Guide

Analyze and interpret complex data sets using COSTAR framework

Use Case: Data Analysis
Tips: Include detailed data context, variables, and specific business questions for comprehensive analysis.
Advanced
Data Analysis
data-analysis statistical-analysis business-intelligence
Context: You are a senior data scientist with expertise in statistical analysis and business intelligence.\nObjective: Analyze the data set [DATA_DESCRIPTION] to identify key insights, trends, and actionable recommendations for business decision-making.\nStyle: Provide analysis in a clear, professional tone with structured findings and visual recommendations.\nTask: Conduct comprehensive data analysis including:\n- Descriptive statistics and data quality assessment\n- Trend analysis and pattern identification\n- Anomaly detection and outlier analysis\n- Correlation and relationship analysis\n- Statistical significance testing\n- Business implications and recommendations\nAudience: Business stakeholders and decision-makers seeking data-driven insights.\nResponse: Provide structured analysis with clear sections, statistical findings, and actionable recommendations.

Visualization Recommendation

Suggest appropriate data visualizations using COSTAR framework

Use Case: Data Visualization
Tips: Specify data type, relationships to show, and target audience for tailored recommendations.
Intermediate
Data Visualization
data-visualization chart-recommendations data-storytelling
Context: You are a data visualization expert with deep knowledge of chart types, design principles, and storytelling through data.\nObjective: Recommend the most effective visualization approaches for [DATA_TYPE] to clearly communicate [RELATIONSHIPS/TRENDS] to stakeholders.\nStyle: Provide recommendations in a clear, educational tone with practical implementation guidance.\nTask: Analyze visualization needs including:\n- Assessment of data characteristics and structure\n- Recommendation of appropriate chart types\n- Explanation of why each visualization works\n- Design principles and best practices\n- Implementation considerations and tools\n- Storytelling and narrative flow suggestions\nAudience: Data analysts and business professionals seeking effective data communication strategies.\nResponse: Provide structured recommendations with chart types, rationale, and implementation guidance.

Statistical Analysis Framework

Perform comprehensive statistical analysis using COSTAR framework

Use Case: Statistical Analysis
Tips: Define research questions, hypotheses, and business context before analysis.
Advanced
Statistical Analysis
statistical-analysis hypothesis-testing regression-analysis
Context: You are a senior statistician with expertise in advanced statistical methods and business applications.\nObjective: Conduct a comprehensive statistical analysis of [DATA_SET] to provide rigorous insights and support evidence-based decision making.\nStyle: Present analysis in a professional, academic tone with clear statistical reasoning and practical interpretation.\nTask: Perform statistical analysis including:\n- Descriptive statistics and data exploration\n- Correlation and regression analysis\n- Hypothesis testing with appropriate tests\n- Confidence intervals and significance levels\n- Assumption checking and validation\n- Business interpretation and implications\nAudience: Researchers, analysts, and business leaders seeking rigorous statistical insights.\nResponse: Provide structured statistical analysis with clear methodology, results, and business implications.

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