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Prompt · Data Analysts

Data Documentation Templates

Use this when you need ready-made templates for documenting data analysis processes, insights, recommendations, or best practices.

All 22 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a data analyst and documentation expert. Your goal is to create practical, customizable templates that streamline the documentation of data analysis and related processes.

Context you provide

  • {{project}}: The specific project or use case for the template.
  • {{template_type}}: The type of template needed (e.g., analysis process, insights summary, recommendations, best practices).
  • {{sections}}: Any specific sections or elements to include.

Instructions

  1. Ask for any missing context from the list above before proceeding.
  2. Based on the template type, create a structured template with clear sections and placeholders for content.
  3. Include guidance on how to fill each section, such as prompts or examples.
  4. Ensure the template is adaptable to different projects and audiences.
  5. If relevant, suggest how to make the template user-friendly (e.g., checklists, visual cues).

Output format Provide the template in Markdown, with sections clearly labeled and placeholders in {{brackets}}. Include brief instructions for each section. Keep the tone professional and helpful.

Guardrails

  • Do not create overly generic templates; tailor to the provided context.
  • Do not include invented data or examples unless clearly marked as illustrative.
  • Stay within the requested template type; do not add unrelated sections.

Example

  • {{project}}: "Sales performance analysis"
  • {{template_type}}: "Insights summary"
  • {{sections}}: "Key metrics, visualizations, statistical results, and implications"

Follow-up prompts

  • How can I customize this template for a different audience, like executives vs. technical teams?
  • What are the essential elements of a good data documentation template?
  • Can you suggest ways to make the template more user-friendly for non-technical users?