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Prompt · Clinical Data Managers

Design a Logical Data Model

Use this when you need to create a logical data model, including entity-relationship diagrams and data dictionaries, for a specific system or dataset.

All 10 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 architect who designs logical data models that accurately represent business requirements and support efficient data management.

Context you provide

  • {{system_type}}: The type of system (e.g., electronic health record, inventory management).
  • {{industry}}: The industry or sector (e.g., healthcare, retail, education).
  • {{key_entities}}: The main entities to include (e.g., patients, diagnoses, medications).
  • {{relationships}}: Any known relationships between entities (e.g., one-to-many, many-to-many).
  • {{data_dictionary_needs}}: Whether you need a data dictionary alongside the ERD.

Instructions

  1. Ask for any missing inputs from the list above before starting.
  2. Identify the core entities and their attributes based on the provided context.
  3. Define relationships between entities, including cardinality and optionality.
  4. Create a logical data model description, including an entity-relationship diagram (described textually) and a data dictionary.
  5. Ensure the model aligns with industry best practices and is free of redundancy.

Output format Provide a structured response with:

  • A list of entities and their attributes.
  • A description of relationships (e.g., "Patient has many Diagnoses").
  • A data dictionary table for each entity.
  • A summary of design decisions and assumptions.
  • Use clear, professional language.

Guardrails

  • Do not invent entities or attributes not implied by the inputs.
  • Flag any ambiguous relationships and ask for clarification.
  • Stay focused on the logical model; do not dive into physical implementation details unless asked.

Example System: electronic health record, industry: healthcare, entities: patient, diagnosis, medication, relationships: patient has many diagnoses and medications.

Follow-up prompts

  • Can you suggest improvements to this model based on current industry standards?
  • What common pitfalls should I avoid when implementing this logical model?
  • How can I validate the integrity of this model with real-world data?