Welcome! This brief survey takes about 6 minutes. Your responses are confidential and reported in aggregate.
Synthetic data refers to artificially generated data (e.g., via simulations or generative models) intended to mimic real data’s statistical properties while protecting sensitive information or filling gaps.
In the last 12 months, have you worked with synthetic data?
- Yes, regularly (monthly or more)
- Yes, occasionally
- No, familiar with the concept
- No, not familiar
Which use cases are most relevant for you or your team? (Select all that apply)
- Prototyping or training ML models
- Class imbalance augmentation
- Privacy-preserving sharing/compliance
- Testing and QA (e.g., edge cases, rare events)
- Synthetic logs or telemetry for load testing
- Analytics demos or sandboxing
- Education or training
Which tools or approaches have you mainly used to generate synthetic data?
Approximately what percentage of data in your projects over the last 12 months was synthetic? Enter a number from 0 to 100.
If compliance or privacy is a priority, briefly describe the data types or regulations you must satisfy (e.g., HIPAA, GDPR).
Max 600 chars
How much demonstrated fidelity/utility do you require before using synthetic data in production?
For each activity, how appropriate is synthetic data in your context?
Rank your top concerns about synthetic data (drag to order).
How likely are you to try synthetic data in the next 6 months?
Which factors most limit your use of synthetic data today? (Select all that apply)
- Hard to evaluate quality/metrics
- Limited domain coverage
- Tooling or integration gaps
- Compute or cost constraints
- Stakeholder skepticism/buy-in
- Policy/legal uncertainty
- No clear need
Allocate 100 points to the improvements that would most accelerate adoption in your org.
Anything else we should know about your limits or ideal use cases for synthetic data?
Max 600 chars
Which best describes your primary role?
- Software engineer
- ML/AI engineer
- Data scientist
- Data/ML platform engineer
- Security/privacy engineer
- Product/engineering manager
- Researcher/academic
- Other
Years of professional experience in software/data roles
What is your primary domain or industry?
- Technology
- Finance/FinTech
- Healthcare/Life sciences
- Retail/Consumer
- Telecom/Media
- Manufacturing/Industrial
- Government/Public sector
- Education
- Other
Organization size (global headcount)
Region you primarily work in
Quality check: To confirm attention, please select “Yes.”
Any final comments or context you want to share?
Max 600 chars
AI Interview: 2 Follow-up Questions on your responses about synthetic data
Thank you for participating! Your input helps us understand practical needs and considerations around synthetic data.