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PUBLIC DATA ENGINEERING PROJECT

Making renewable-energy data orchestration observable.

An end-to-end renewable-energy business-intelligence pipeline that uses Airflow to make ingestion, transformation and serving dependencies explicit and repeatable.

AirflowSnowflakePythonSQLDockerBI
01 / EVIDENCE TRACE

Follow each claim through the system.

ARCHITECTURE.MAPSelect any component to inspect it.
The cyan connection shows where the selected evidence enters the system.
INSPECTINGBI

The serving layer connects engineering work with a consumable outcome.

Connected to selected evidence
02 / ENGINEERING DECISIONS

Why the architecture looks this way.

01

Orchestration is documentation

A well-designed DAG makes data dependencies and recovery behavior visible.

02

Separate movement from meaning

Ingestion, transformation and serving layers change for different reasons.

03

Design for reruns

Repeatable tasks and explicit dependencies make failure recovery less surprising.

CLAIM.BOUNDARY

Credibility includes saying what the work does not prove.

A public engineering project that demonstrates source-to-BI architecture and implementation. It does not establish production-scale throughput, availability or business impact.

NEXT CASE STUDYAI-BOOST CHALLENGE 3 · SOLO RESEARCH POCEvidence decides what AI is allowed to release.