  For any business, planning is a continuous process, and typically
business-owners focus on making both long-term planning aligned with a
particular strategy as well as short-term planning that accommodates the
dynamic market situations. An ability to perform an accurate financial forecast
is crucial for effective planning. In this paper, we focus on providing an
intelligent and efficient solution that will help in forecasting revenue using
machine learning algorithms. We experiment with three different revenue
forecasting models, and here we provide detailed insights into the methodology
and their relative performance measured on real finance data. As a real-world
application of our models, we partner with Microsoft's Finance organization
(department that reports Microsoft's finances) to provide them a guidance on
the projected revenue for upcoming quarters.
