In this video, we will present how Dremio Data Lakehouse came to the rescue when a use case from the electricity retail domain with a large scale machine learning problem around power consumption forecasting imposed some significant challenges on the data engineering and data science teams in Shell.
We will describe how we:
1.) addressed the large variety of data sources that needed to be ingested, processed and served to the Data Science team
2.) streamlined some of the Data Science workflows around data exploration, feature engineering and model testing
3.) operationalized and scaled ML training and inferencing