Transforms the Way Businesses Use Data and Generate Meaningful Insights
Synthetic data is data generated artificially based on data collected from real-world occurrences. It is artificially generated data in the form of text, tables, images, and videos, among others. Synthetic data generation will address the challenge of inefficient datasets and privacy concerns.
Generated using algorithms, it enables organizations to test operational data and train artificial intelligence (AI)/machine learning (ML) models efficiently. It also helps validate mathematical models and train deep learning models. The technology will go mainstream in the next 5 years, considering the global adoption of AI/ML models to elevate operations. There is constant R&D and reinforcement for building synthetic data in a standardized format.
In this study, the publisher will assess the transformation due to data usage caused by artificially generated data. This research covers the following:
- Models and techniques to generate synthetic data
- Existing and emerging ecosystems
- Technology-related developments and global trends
- Growth opportunities
- Strategic insights and viewpoints
