Synthetic data creates realistic datasets without exposing sensitive personal or proprietary information risks.Data scientists use synthetic data to overcome scarcity, imbalance, and limited edge cases.Synthetic generation improves model robustness by simulating rare events and extreme scenarios effectively.Privacy regulations become easier as synthetic datasets avoid storing real user identities directly.Faster experimentation occurs when teams generate data instantly instead of lengthy collection processes.Synthetic data enables safer data sharing across partners, vendors, and global research teams.AI training benefits as synthetic data reduces bias and balances underrepresented classes better.Industries like healthcare and finance adopt synthetic data to meet compliance demands globally.Future data science workflows blend real and synthetic data for optimal performance outcomes.Read More Stories.Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp