Discussing what uses algorithmically generated data has and experimenting with its implementation in models.

Synthetic data is the use of statistics or algorithms to produce a facsimile of an original dataset or element. The key premise is that the data is not shared, but its statistical properties are, along with the presence of anomalies like outliers.

Most synthetic data is seen as being useful for preserving privacy or anonymity, by allowing the development of dashboards or algorithms without divulging the dataset to the developers, or for use in non-production environments for similar reasons.

Additional use cases outside the privacy realm could be exploring niche permutations of data; synthesizing data to represent an edge condition…

Paul Bruffett

Enterprise Architect specializing in data and analytics.

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