Data Science Powered Financial Planning & Forecasting

Join us for this behind-the-scenes look at how Snowflake’s Finance team uses the Data Cloud to power their corporate planning cycle, including forecasting revenue and other critical metrics.

For many businesses, including consumption-based businesses like Snowflake, ad-driven companies, and professional service companies, predicting revenue and other top line metrics can be far from straightforward. Traditional excel-driven forecasting requires immense amounts of effort to deliver quarterly forecasts and SaaS planning tools leave teams with siloed data that is difficult to utilize cross-functionally.

Being able to accurately predict revenue was a prerequisite for Snowflake to become a publicly traded company. Using the Data Cloud, the Snowflake Finance Team was able to centralize product data, enterprise resource planning (ERP) data, and other business system data, and develop data science models to predict revenue for each customer daily.

In this session, Andrew Seitz, Director of Data and Analytics for Finance and Matt Franking, Manager of Data Science for Finance will dive into how they use the Data Cloud to improve forecasting accuracy and efficiency.

Join us to learn how:

• Snowflake centralizes billing systems, ERP data, product and business data models to create a holistic view of the business.
• Snowflake develops and revises forecasting models
• The Data Cloud can help power your corporate planning cycle