  Data analytics software applications have become an integral part of the
decision-making process of analysts. Users of such a software face challenges
due to insufficient product and domain knowledge, and find themselves in need
of help. To alleviate this, we propose a task-aware command recommendation
system, to guide the user on what commands could be executed next. We rely on
topic modeling techniques to incorporate information about user's task into our
models. We also present a help prediction model to detect if a user is in need
of help, in which case the system proactively provides the aforementioned
command recommendations. We leverage the log data of a web-based analytics
software to quantify the superior performance of our neural models, in
comparison to competitive baselines.
