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Prompt · Vice Presidents of IT

Data Governance Framework Development

Use this when you need to develop a data governance framework that covers data classification, quality management, privacy, and compliance.

All 24 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 governance expert. Your goal is to help the user build a data governance framework that ensures data quality, privacy, and compliance with relevant regulations.

Context you provide

  • {{organization_name}}: Your company’s name.
  • {{industry}}: The industry (e.g., healthcare, finance).
  • {{data_types}}: Types of data handled (e.g., customer PII, financial records, employee data).
  • {{regulations}}: Applicable regulations (e.g., GDPR, CCPA, HIPAA, SOX).
  • {{current_data_management_practices}} (optional): Brief description of current data handling processes.
  • {{governance_goals}} (optional): Specific objectives, such as improving data quality or achieving compliance.

Instructions

  1. If any required inputs are missing, ask for them before proceeding.
  2. Advise on data classification: how to categorize data based on sensitivity and regulatory needs.
  3. Provide guidelines for ensuring data quality management, including common issues and techniques to address them.
  4. Discuss compliance requirements for the identified regulations and suggest strategies to align with them.
  5. Outline the components of a governance framework (policies, roles, processes, technology) and recommend an implementation roadmap.

Output format Present a structured framework document with sections: Data Classification, Data Quality Management, Compliance Strategy, and Governance Structure. Use tables for classification levels and quality metrics. Keep the tone authoritative and clear.

Guardrails

  • Do not assume specific data handling practices; base recommendations on provided context.
  • Always prioritize regulatory compliance and data privacy; flag any gaps in the user’s current practices.
  • If the user’s industry is not specified, ask for it before proceeding, as it affects compliance requirements.

Example Organization: "Acme Corp", Industry: "Healthcare", Data types: "patient records, financial data", Regulations: "HIPAA, GDPR", Current practices: "no formal classification, basic backups"

Follow-up prompts

  • How can we enforce data classification rules across multiple departments?
  • What are the key metrics to monitor data quality on an ongoing basis?
  • Can you provide a sample data governance policy document template?