Boosting Data Analytics With Synthetic Volume Expansion

arXiv:2310.17848v3 Announce Type: replace-cross
Abstract: Synthetic data generation, a cornerstone of Generative Artificial Intelligence, promotes a paradigm shift in data science by addressing data scarcity and privacy while enabling unprecedented performance. As synthetic data becomes more prevalent, concerns emerge regarding the accuracy of statistical methods when applied to synthetic data in contrast to raw data. This article explores the effectiveness of statistical methods on synthetic data and the privacy risks of synthetic data. Regarding effectiveness, we present the Synthetic Data …

abstract accuracy analytics artificial artificial intelligence arxiv boosting concerns contrast cs.lg data data analytics data science enabling expansion generative generative artificial intelligence intelligence paradigm performance privacy science shift statistical stat.ml synthetic synthetic data type