With accurate maps and weather information, captains are more likely to steer their ships through choppy waters safely. Similarly, with more accurate revenue forecasts, business leaders are more likely to guide and grow their businesses safely through challenging conditions.

With the rise of consumption-based pricing models, a renewed focus on the usage data is needed to have predictable models. In this session we will demonstrate how to forecast revenue for usage-based applications, using a modern datalake approach. We will compare multiple ML models to forecast consumption for various common use cases such as compute hours, storage, API calls, and monthly active users (MAUs).