Synthetic Data

Artificially created data that mimics real-world information

Overview

Synthetic data is artificially created information that looks and behaves like real data. It's useful when real data is hard to get, expensive, or when privacy is important.

Why Use Synthetic Data?

Synthetic data helps when:

  • Real data is scarce
  • Privacy is crucial
  • Testing edge cases
  • Balancing datasets
  • Protecting sensitive information
  • Reducing data collection costs

How It's Created

  • Using statistical patterns
  • Generating from rules
  • Learning from real data
  • Simulating scenarios
  • Following privacy rules
  • Preserving relationships

Common Uses

  • Testing software
  • Training AI models
  • Privacy protection
  • Data augmentation
  • Edge case testing
  • Research and development

Best Practices

  • Validate quality
  • Check for realism
  • Preserve relationships
  • Test thoroughly
  • Document methods
  • Monitor usefulness