Case Study: Shell achieves faster, scalable electricity forecasting with Dremio

Shell processes 6–8B records in minutes with Dremio

Shell, a global energy company, faced a significant data challenge as the energy sector transformed. Their power retail organization needed to process enormous volumes of data from decentralized renewable sources to create accurate electricity consumption forecasts. They required a solution to handle billions of records within minutes for production models without the delays of complex ETL pipelines. Dremio's data lakehouse platform was selected to address this need for scale and speed.

Using Dremio as a unified compute engine, Shell was able to directly access distributed data sources, accelerating forecasting model development. The solution enabled them to successfully process 6-8 billion records within minutes to run over 100 concurrent production models. Dremio provided significant performance gains, eliminated weeks of ETL development time, and evolved into a comprehensive data mesh architecture for the organization.

Shell