  Sharing data can often enable compelling applications and analytics. However,
more often than not, valuable datasets contain information of a sensitive
nature, and thus, sharing them can endanger the privacy of users and
organizations. A possible alternative gaining momentum in both the research
community and industry is to share synthetic data instead. The idea is to
release artificially generated datasets that resemble the actual data -- more
precisely, having similar statistical properties. In this article, we provide a
gentle introduction to synthetic data and discuss its use cases, the privacy
challenges that are still unaddressed, and its inherent limitations as an
effective privacy-enhancing technology.
