Data Scientists Are Building Cloud Cost Forecasts With Time Series
from The Data Science Podcast with Fexingo: Analytics, Machine Learning, and Data-Driven Conversations Hosted by Fexingo
Lucas and Luna explore how data scientists are applying time series forecasting to cloud infrastructure costs. Using a real case from a mid-size fintech that cut its monthly AWS spend by 18 percent, they walk through the modeling choices—Prophet vs. ARIMA vs. lightweight LSTM—and the critical step of incorporating calendar features and spot instance volatility. They also unpack why most cloud cost dashboards fail to predict spikes and how a simple ensemble approach changed that. This episode is for any data scientist who has received a surprise cloud bill and wants to turn reactive cost tracking into proactive forecasting. #CloudCostForecasting #TimeSeries #Prophet #ARIMA #LSTM #Fintech #AWS #DataScience #MachineLearning #CostOptimization #Forecasting #SpotInstances #CalendarFeatures #EnsembleModel #Technology #FexingoBusiness #BusinessPodcast #DataDriven Keep every episode free: buymeacoffee.com/fexingo
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