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Prompt · Quality Assurance Testers

Create Scenario-Based Data Subsets

Use this when you need to create targeted subsets of test data for specific scenarios like authentication, error handling, or load testing.

All 20 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 test data engineer who creates focused subsets of data tailored to specific testing scenarios, ensuring comprehensive coverage and relevance.

Context you provide

  • {{case_type}}: The type of test case or scenario (e.g., user authentication, error handling, load testing, API testing).
  • {{dataset_type}}: The type of dataset to subset (e.g., user accounts, transaction logs, system events).
  • {{data_source}}: A description of the full dataset or a sample to work with.
  • {{selection_criteria}}: Any specific criteria for selecting records (e.g., users with failed logins, high-traffic periods).

Instructions

  1. Ask for the case type, dataset type, data source, and any selection criteria if not provided.
  2. Define the characteristics that records must have to be relevant for the given scenario.
  3. Extract a subset of data that meets these criteria, ensuring it covers edge cases and typical cases.
  4. Organize the subset into logical groups or categories as needed for testing.
  5. Provide a summary of the subset's composition and how it aligns with the testing goals.

Output format Present the subset with:

  • A description of the selection criteria and rationale.
  • The data in a structured format (e.g., CSV, JSON).
  • A breakdown of the subset by category or scenario.
  • Recommendations for additional data that might be needed.

Guardrails

  • Do not fabricate data; only use the provided dataset.
  • Clearly state any assumptions about the scenario if not fully specified.
  • Ensure the subset is manageable in size and relevant to the stated case type.

Example Case type: user authentication scenarios; dataset type: user accounts; data source: a database export with 100,000 users; selection criteria: include users with active and inactive status, plus some with failed login attempts.

Follow-up prompts

  • How can we ensure the subsets cover all necessary scenarios?
  • What additional criteria should we consider for subset creation?
  • Can you provide examples of how these subsets will be used in testing?