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Case Study — E.ON · Energy Sector

Automation of Real-Time Data Pipelines for Dynamic Pricing Systems

Data processing automation for dynamic pricing within the European energy market.

[Data Engineering] [Production Released] [Energy]

The Client

E.ON Energie Deutschland GmbH is one of the leading players in the European energy sector.

The Challenge

Eliminate manual errors in daily data preparation for highly complex mathematical pricing models and accelerate development cycles for new data streams.

Our Solution

  • Pipeline Architecture

    Design and deployment of highly scalable and robust ELT pipelines based on Snowflake and Azure.

  • Orchestration

    Implementation of a dbt development model combined with Dagster for consistent transformations.

  • Data Lineage

    Development of a fully automated generation of data dependencies (Data Lineage) to increase comprehensibility for internal business analysts.

Results

Measurable Results

Quality
Reduction of erroneous data records within the production pipelines by 15%.
Time Savings
Reduction of development time for new data pipelines by 50%.
Efficiency
Drastically simplified troubleshooting through transparent data structures and visualization of pipeline-critical metrics in Grafana.

Schedule Consultation

Your project as the next success story.

Just like for E.ON, we design, implement, and stabilize mission-critical data platforms – compliant-by-design.