  Many researchers have explored tools that aim to recommend data insights to
users. These tools automatically communicate a rich diversity of data insights
and offer such insights for many different purposes. However, there is a lack
of structured understanding concerning what researchers of these tools mean by
"insight" and what tasks in the analysis workflow these tools aim to support.
We conducted a systematic review of existing systems that seek to recommend
data insights. Grounded in the review, we propose 12 types of automated
insights and four purposes of automating insights. We further discuss the
design opportunities emerged from our analysis.
