In our digital economy, data is the currency and catalyst that drives growth and innovation. All AI initiatives rely on data to build models, and increasingly all organizations’ decisions are data-driven. Access to high-quality data that is clean, complete, and context-specific is what powers these processes.
The catch: data access and data accuracy are hard to come by.
Organizations are turning to synthetic data as a valuable solution enabled by generative AI to overcome pressing challenges with data access, quality, and availability.
In this guide, we explore:
- The promise of synthetic data and its key benefits
- Models and technologies that power synthetic data generation
- Practical enterprise use cases of synthetic data, including real-world examples of its use in mission-critical applications
