EnergySourced

Case Study: E.ON cuts time-to-insight by 95% with Dremio's lakehouse platform

E.ON Case StudySourced & dated by Case Study Desk

Key facts · TL;DR

Company

E.ON

Industry

Energy

Challenge

Queries taking days, once-daily data

Headline result

E.ON's Nordic division achieved a 95% reduction in time-to-insight and refreshed data every 15 minutes with Dremio.

Key results

95%

Reduction in time-to-insight (queries in ~10 min)

15 min

Data freshness, improved from once daily

The challenge

E.ON's Nordic division, serving over 1 million customers, ran a complex data infrastructure where queries took up to a week, data refreshed only once per day, and business users lacked self-service access to explore data.

The solution

E.ON modernized on Dremio's Unified Lakehouse Platform, replacing Cassandra and Oracle with a Dremio-powered lake on Kubernetes in Azure, using Reflections, Iceberg tables, and dbt for governed self-service analytics.

“Our data infrastructure was becoming a bottleneck. We needed a solution to handle our growing data volumes, provide faster insights, and enable self-service for our business users.”
M
Mattias
Head of Department for Data, Engineering, and Platforms, E.ON

The results, in context

Time-to-insight dropped 95%, with queries now completing in about 10 minutes instead of several days. Data freshness improved from once daily to every 15 minutes, enabling near real-time analysis and SQL-based self-service.

Products used

Dremio Dremio Unified Lakehouse PlatformDremio Dremio ReflectionsDremio Apache Iceberg