Business functions that can benefit from synthetic data include:
- Marketing: Synthetic data allows marketing units to run detailed, individual-level simulations to improve their marketing spend. Such simulations would not be allowed without user consent due to GDPR however synthetic data, which follows the properties of real data, can be reliably used in simulation
- Machine learning: Self driving car simulations pioneered the use of synthetic data.
- Agile development and DevOps: When it comes time for software testing and quality assurance, artificially generated data is often the better choice as it eliminates the need to wait for ‘real’ data. Often referred to under this circumstance as ‘test data’. This can ultimately lead to decreased test time and increased flexibility and agility during development
- Clinical and scientific trials: Synthetic data can be used as a baseline for future studies and testing when no real data yet exists.
- Research: To help better understand the format of real data not yet recorded, develop an understanding of its specific statistical properties, tune parameters for related algorithms, or build preliminary models.
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Security: Synthetic data can be used to secure organizations’ online & offline properties. Two methods are commonly used:
- Training data for video surveillance: To take advantage of image recognition, organizations need to create and train neural network models but this has two limitations: Acquiring the volumes of data and manually tagging the objects. Synthetic data can help train models at lower cost compared to acquiring and annotating training data.
- Deep-fakes: Deep fakes can be used to test face recognition systems