100 ChatGPT Prompts for Data Analysts [Free Templates]

You stare at the ChatGPT box. You type "analyze this data." You get generic garbage. The problem isn't ChatGPT — it's your prompts. Great data analysis prompts are specific, methodical, and insight-focused. I've curated 100 battle-tested prompts across 10 categories. Copy, paste, analyze smarter.

Data Cleaning Prompts (12)

1. Data Cleaning Script

Write a Python script to clean this dataset:
[paste data sample or describe columns]
Include: missing values, duplicates, outliers, type conversions, validation.
Tool: [pandas/SQL/R].

2. Missing Value Strategy

Develop a strategy for handling missing values in this dataset:
[describe columns and % missing]
Include: analysis of missing pattern, imputation methods, impact assessment, recommendations.

3. Data Validation Rules

Create data validation rules for [dataset/columns].
Include: range checks, format validation, consistency checks, business rules, error handling.

4. Duplicate Detection & Removal

Write a duplicate detection script for this data:
[describe data structure]
Include: exact matches, fuzzy matching, deduplication strategy, logging changes.

5. Outlier Detection & Treatment

Detect and treat outliers in [column/dataset]:
[describe data and context]
Include: detection methods (IQR/Z-score/DBSCAN), treatment options, justification.

6. Data Type Optimization

Optimize data types for this dataset:
[describe columns and current types]
Include: memory reduction, type conversions, categorical encoding, datetime parsing.

7. Text Data Cleaning

Clean this text data column: [describe column]
Include: lowercase, remove special chars, normalize, stemming/lemmatization, stopwords.

8. Date/Time Parsing & Normalization

Parse and normalize inconsistent dates in this column:
[sample values]
Include: format detection, timezone handling, missing dates, feature extraction.

9. Categorical Data Normalization

Normalize categorical data in this column:
[sample values with inconsistencies]
Include: standardization, mapping, encoding strategy, new category handling.

10. Data Quality Report

Generate a data quality report for [dataset]:
Include: completeness, accuracy, consistency, timeliness, validity scores, recommendations.

11. ETL Pipeline Design

Design an ETL pipeline for [data source] to [destination].
Include: extraction, transformation steps, loading, scheduling, error handling, monitoring.

12. Data Reconciliation Script

Write a data reconciliation script comparing [source] and [target] datasets.
Include: key matching, field comparison, discrepancy reporting, resolution workflow.
## SQL Queries (12)

### 13. Complex SQL Query

Write a SQL query to [analyze/join/aggregate] from these tables: [describe tables and relationships] Include: joins, window functions, CTEs, performance optimization.

### 14. Window Function Query

Write a window function query for [analysis purpose]: [describe data and desired output] Include: ROW_NUMBER, RANK, LAG/LEAD, running totals, partitioning.

### 15. Data Aggregation Query

Write an aggregation query for [metrics] by [dimensions]: [describe tables and columns] Include: GROUP BY, HAVING, subqueries, ordering, formatting.

### 16. Cohort Analysis Query

Write a cohort analysis SQL query for [user/customer] retention: [describe tables] Include: cohort definition, retention calculation, time periods, output format.

### 17. Funnel Analysis Query

Write a funnel analysis query for [user journey]: [describe event tables] Include: step definitions, conversion rates, drop-off analysis, time windows.

### 18. Data Quality Check Query

Write SQL queries to check data quality for [table/columns]: Include: null checks, range validation, uniqueness, referential integrity, anomalies.

### 19. Time Series Query

Write a time series query for [metric] over [time period]: [describe tables] Include: date truncation, period-over-period comparison, rolling averages.

### 20. Ranking Query

Write a ranking query for [entity] by [metric]: [describe tables] Include: top N, percentile ranking, dense rank, handling ties.

### 21. Pivot/Crosstab Query

Write a pivot query to reshape this data: [describe current structure and desired output] Include: conditional aggregation, pivot logic, ordering.

### 22. Incremental Load Query

Write an incremental load query for [table] from [source]: [describe schema] Include: change detection, delta extraction, merge/upsert logic.

### 23. Performance Optimization

Optimize this slow SQL query: [paste query] Include: index suggestions, query rewrite, execution plan analysis, alternatives.

### 24. Report Query Template

Write a report-ready SQL query for [business report]: [describe requirements] Include: formatted output, calculated fields, comparisons, sorting, limit.

Statistical Analysis (12)

25. Descriptive Statistics Report

Generate a descriptive statistics report for [dataset/columns].
Include: mean, median, mode, std dev, skewness, kurtosis, quartiles, distribution shape.

26. Hypothesis Test Selection

Recommend a hypothesis test for this question: [describe question]
Include: test type, assumptions, null/alternative hypotheses, interpretation, sample size.

27. Correlation Analysis

Perform correlation analysis on these variables: [list variables]
Include: correlation method, significance testing, visualization, multicollinearity check.

28. Regression Analysis

Build a regression model for [target] using [predictors]:
[describe dataset]
Include: model selection, diagnostics, interpretation, assumptions checking, improvement.

29. A/B Test Design

Design an A/B test for [experiment]:
Include: hypothesis, sample size calculation, metrics, duration, randomization, analysis plan.

30. A/B Test Analysis

Analyze these A/B test results:
[describe/control data, treatment data, metrics]
Include: statistical significance, effect size, confidence intervals, recommendations.

31. Segmentation Analysis

Perform customer segmentation analysis on [dataset]:
Include: feature selection, clustering method, segment profiling, validation, actionable insights.

32. Trend Analysis

Analyze trends in [metric] over [time period]:
[describe data]
Include: trend detection, seasonality, cyclical patterns, forecasting, anomalies.

33. Distribution Analysis

Analyze the distribution of [variable] in [dataset]:
Include: distribution type, normality tests, transformations, visualization recommendations.

34. Sample Size Calculator

Calculate the sample size needed for [study type]:
Include: effect size, confidence level, power, one/two-tailed, population size adjustment.

35. Statistical Significance Interpretation

Interpret these statistical results for a business audience:
[paste results]
Include: plain language explanation, practical significance, limitations, recommendations.

36. Experimental Design Review

Review this experimental design for [study]:
[describe design]
Include: validity threats, randomization, control, bias, improvements, analysis approach.
## Visualization (10)

### 37. Chart Selection Guide

Recommend the best chart type for visualizing [data type] showing [relationship]. Include: chart options, when to use each, tools, accessibility considerations.

### 38. Dashboard Wireframe

Create a dashboard wireframe for [business purpose] with [key metrics]. Include: layout, chart types, filters, KPIs, drill-down paths, user flow.

### 39. Data Storytelling Narrative

Create a data storytelling narrative for this analysis: [paste key findings] Include: hook, context, insights, visuals description, call to action.

### 40. Visualization Code (Python/R)

Write code to visualize this analysis: [describe data and desired visualization] Include: matplotlib/plotly/ggplot2 code, styling, annotations, export settings.

### 41. Color Palette for Data Visualization

Create a color palette for [dashboard/report] with [accessibility requirements]. Include: primary/secondary colors, colorblind-safe, semantic colors, usage guidelines.

### 42. Interactive Dashboard Design

Design an interactive dashboard for [audience] using [tool — Tableau/Power BI/Looker]. Include: interactivity, filters, drill-downs, mobile responsiveness, performance.

### 43. KPI Card Design

Design KPI cards for [metric set] on [dashboard]. Include: value, trend, comparison, sparkline, color coding, formatting, thresholds.

### 44. Report Layout Template

Create a report layout template for [audience — executives/operations/etc]. Include: structure, visual hierarchy, chart placement, narrative flow, action items.

### 45. Data Visualization Best Practices Review

Review this visualization for best practices: [describe or paste visualization] Include: clarity, accuracy, efficiency, aesthetics, accessibility, improvements.

### 46. Geographic Data Visualization

Create a geographic visualization plan for [spatial data]. Include: map type, data encoding, granularity, interaction, color scheme, tools.

Report Writing & Dashboards & Business Intelligence & Predictive Analytics (66)

47. Executive Summary

Write an executive summary for this analysis:
[paste key findings]
Include: context, methodology, key findings, recommendations, next steps.
Length: 200-300 words.

48. Analysis Report Outline

Create an analysis report outline for [business question] using [data source].
Include: sections, key points per section, visualizations, appendices.

49. Findings Translation to Business Language

Translate these technical findings into business language:
[paste technical findings]
Include: plain language, impact statement, action items, urgency level.

50. Data-Driven Recommendation Memo

Write a data-driven recommendation memo for [decision]:
Include: situation, analysis summary, options considered, recommendation, expected impact.

51. Weekly/Monthly Report Template

Create a [weekly/monthly] reporting template for [metric set].
Include: KPIs, trends, comparisons, highlights, concerns, actions, forecast.

52. Data Dictionary Creation

Create a data dictionary for [dataset/table].
Include: column names, types, descriptions, business rules, sample values, owners.

53. Metric Definition Document

Define [number] business metrics for [organization]:
Include: formula, data source, calculation logic, business meaning, owner, refresh frequency.

54. Dashboard Requirements Document

Create a requirements document for [dashboard type] for [audience].
Include: users, use cases, KPIs, data sources, filters, refresh schedule, success criteria.

55. BI Tool Comparison

Compare BI tools for [use case]: [Tool A] vs [Tool B] vs [Tool C].
Include: features, pricing, ease of use, scalability, integration, recommendation.

56. Automated Report Generation

Design an automated report generation pipeline for [report type].
Include: data extraction, transformation, visualization, distribution, scheduling, monitoring.

57. Data Governance Framework

Create a data governance framework for [organization/team].
Include: ownership, quality standards, access control, lineage, compliance, tools.

58. Data Pipeline Monitoring

Design monitoring for [data pipeline].
Include: health checks, SLAs, alerting, failure recovery, logging, dashboards.

59. Predictive Model Requirements

Define requirements for a predictive model targeting [business outcome].
Include: objective, features, target variable, success metrics, constraints, timeline.

60. Feature Engineering Guide

Create a feature engineering guide for [dataset/problem].
Include: feature ideas, transformations, encoding, selection methods, validation.

61. Model Evaluation Framework

Create a model evaluation framework for [model type] predicting [target].
Include: metrics, cross-validation, baseline comparison, business impact, monitoring.

62. Forecasting Model Design

Design a forecasting model for [business metric] at [frequency].
Include: data requirements, model selection, seasonality handling, accuracy metrics, updates.

63. Churn Prediction Framework

Design a customer churn prediction framework for [business].
Include: definition, features, model, validation, action triggers, monitoring.

64. Customer Lifetime Value Analysis

Design a CLV analysis for [business] with [data available].
Include: calculation method, segments, prediction, business applications, visualization.

65. Anomaly Detection System

Design an anomaly detection system for [metric/process].
Include: detection method, thresholds, alerting, investigation workflow, false positive handling.

66. Data Monetization Strategy

Create a data monetization strategy for [organization] with [data assets].
Include: internal value, external opportunities, privacy, governance, implementation.

67. Analytics Maturity Assessment

Create an analytics maturity assessment for [organization].
Include: maturity levels, current state, gap analysis, roadmap, investment priorities.

68. Self-Service Analytics Enablement

Design a self-service analytics program for [organization/department].
Include: tool selection, training, governance, templates, support, success metrics.

69. Data Literacy Training Program

Create a data literacy training program for [audience].
Include: curriculum, modules, hands-on exercises, assessment, resources, timeline.

70. Analysis Prioritization Framework

Create a framework for prioritizing analysis requests for [team].
Include: scoring criteria, business impact, effort estimation, capacity planning, SLAs.

71-100: (continuing pattern)

71. Cohort Retention Analysis Design

Design a cohort retention analysis for [product/service].
Include: cohort definition, retention curves, comparison dimensions, actionable insights.

72. Market Basket Analysis

Design a market basket analysis for [retail/e-commerce] with [transaction data].
Include: association rules, support/confidence/lift, recommendations, implementation.

73. Price Elasticity Analysis

Design a price elasticity analysis for [product/service].
Include: data requirements, model approach, segment effects, business applications.

74. Marketing Attribution Model

Design a marketing attribution model for [channels/campaigns].
Include: data requirements, model types, implementation, validation, insights.

75. Demand Forecasting Dashboard

Design a demand forecasting dashboard for [supply chain/retail].
Include: forecast accuracy, trend visualization, scenario planning, alerts.

76. Survey Data Analysis Guide

Create a survey data analysis guide for [survey type].
Include: response cleaning, weighting, statistical analysis, visualization, reporting.

77. Data Exploration Checklist

Create an exploratory data analysis checklist for new datasets.
Include: structure, distributions, relationships, anomalies, assumptions, documentation.

78. Statistical Modeling Assumptions Guide

Create a guide for checking statistical modeling assumptions for [model type].
Include: assumptions, testing methods, violations, remedies, diagnostics.

79. Competitor Benchmarking Analysis

Design a competitor benchmarking analysis using [data sources].
Include: metrics, data collection, comparison framework, insights, visualization.

80. Risk Scoring Model Design

Design a risk scoring model for [risk type] in [context].
Include: risk factors, scoring methodology, calibration, validation, monitoring.

81. Data Quality Improvement Plan

Create a data quality improvement plan for [dataset/organization].
Include: current state, root causes, improvement initiatives, metrics, timeline.

82. Analytics Project Proposal Template

Create an analytics project proposal for [business question].
Include: background, objectives, approach, data needs, timeline, expected value.

83. Stakeholder Communication Framework

Create a communication framework for analytics projects with [stakeholder types].
Include: frequency, format, language level, feedback loops, escalation.

84. Data Migration Validation Guide

Create a data migration validation guide for [source] to [target].
Include: validation checks, reconciliation, performance testing, rollback plan.

85. Streaming Data Analysis Design

Design a streaming data analysis pipeline for [use case].
Include: architecture, tools, latency requirements, scalability, monitoring.

86. Geospatial Analysis Framework

Design a geospatial analysis for [location-based question].
Include: data sources, tools, spatial methods, visualization, applications.

87. Text Analytics Pipeline

Design a text analytics pipeline for [text data — reviews/support tickets/etc].
Include: preprocessing, NLP techniques, sentiment analysis, topic modeling, visualization.

88. Data Visualization Style Guide

Create a data visualization style guide for [team/organization].
Include: chart standards, color palette, typography, labeling, templates, tools.

89. Machine Learning Pipeline Design

Design an ML pipeline for [prediction problem].
Include: data prep, feature engineering, model training, evaluation, deployment, monitoring.

90. Analytics Capacity Planning

Create an analytics capacity plan for [team] handling [workload].
Include: resource needs, skill gaps, tool requirements, budget, timeline.

91. Data Lake/Warehouse Design

Design a data lake/warehouse architecture for [organization].
Include: architecture, schema design, ETL, governance, access, scalability.

92. Business KPI Monitoring System

Design a KPI monitoring system for [department] tracking [metrics].
Include: data sources, refresh frequency, alerting, dashboards, ownership.

93. Analytics ROI Measurement

Create a framework for measuring analytics ROI for [organization].
Include: value metrics, cost tracking, attribution, reporting, improvement cycle.

94. Data Science Project Lifecycle

Document the data science project lifecycle for [team].
Include: phases, deliverables, review gates, tools, roles, timelines.

95. Automated Insight Generation

Design an automated insight generation system for [metrics/dashboards].
Include: anomaly detection, trend alerts, comparison insights, narrative generation.

96. Cross-Functional Analytics Collaboration

Design a cross-functional analytics collaboration model with [teams].
Include: request process, SLAs, knowledge sharing, governance, communication.

97. Analytics Documentation Standards

Create analytics documentation standards for [team].
Include: analysis templates, code documentation, data dictionaries, decision logs.

98. Performance Testing Guide

Create a performance testing guide for [data system/pipeline].
Include: load testing, stress testing, benchmarks, monitoring, optimization.

99. Data Privacy by Design Guide

Create a data privacy by design guide for analytics projects in [regulation — GDPR/CCPA/etc].
Include: privacy principles, data minimization, anonymization, consent, audit.

100. Analytics Career Development Framework

Create a career development framework for data analysts at [level — junior/senior/staff].
Include: skills matrix, growth path, learning resources, mentorship, evaluation criteria.

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## How to Use These Prompts

1. **Copy the prompt** — Don't modify the structure
2. **Fill in the brackets** — Replace [placeholders] with your data specifics
3. **Provide data context** — Describe schemas, sample values, business context
4. **Specify your tools** — Python, R, SQL, Tableau, Power BI
5. **Iterate on outputs** — Refine based on data specifics

## Pro Tips

- **Always validate assumptions** — Check data distributions before analysis
- **Start simple** — Basic analysis before complex modeling
- **Document everything** — Assumptions, decisions, code, results
- **Communicate in business language** — Stakeholders need insights, not code
- **Automate repetitive tasks** — Scripts, templates, dashboards

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*Get more prompts with our [100 ChatGPT Prompts for Software Developers](/blog/100-chatgpt-prompts-software-developers-2026) or explore [179 Best Free Online Tools](/blog/179-best-free-online-tools-2026) for data analysis tools.*

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