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Case Study — Encavis AG · Renewable Energy

IoT Real-Time Pipelines for Renewable Energy Installations

IoT real-time data processing and time series optimization utilizing Prefect and Snowflake.

[Data Engineering] [Production Released] [Energy]

The Client

Encavis AG is a leading, publicly listed operator of solar parks and onshore wind farms in Europe.

The Challenge

Continuous, zero-latency acquisition, storage, and evaluation of high-frequency IoT sensor data from numerous European energy generation plants.

Our Solution

  • IoT Data Lakehouse

    Establishment of a state-of-the-art, hybrid Data Lakehouse architecture utilizing Snowflake for the ingestion of structured and unstructured time series data.

  • Real-Time Ingestion

    Implementation of continuous data streams directly into the data platform using Snowpipe.

  • Multithreading Pipelines

    Development of bespoke ingestion scripts in Python employing Prefect and dbt for the high-performance orchestration of parallel data processes.

Results

Measurable Results

Optimization
Substantial performance enhancement in processing complex, time-critical sensor data via multithreaded data execution.
Decision Capability
The creation of stable real-time data streams enables the operator to conduct faultless ad-hoc analytics and direct yield monitoring.

Schedule Consultation

Your project as the next success story.

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