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Big Data Processing
Storage, processing and query architectures for data volumes that outgrow conventional tools.
Terra · Infrastructure · Service 4 of 5 · Semantic layer
Reliable movement and transformation of data between sources, platforms and consumers.
data-pipelinesSemantic layer
Data Pipelines
Pipelines are versioned, tested and observable like any other software, with lineage recorded so that anyone can trace a number on a dashboard back to the system it came from.
Capabilities
| # | Capability | Scope of work |
|---|---|---|
| 01 | Ingestion | Change data capture, API and file ingestion, event streaming from devices and applications. |
| 02 | Transformation | Modelled transformations with tests, documentation and lineage. |
| 03 | Orchestration | Scheduling, dependencies, retries and backfills with clear failure handling. |
| 04 | Quality and observability | Data contracts, freshness and anomaly monitoring, alerting to owners. |
In the Operational Model
Pipelines connect the foundation layer to the semantic layer: they are how raw records become the unified objects the rest of the model relies on, and how results travel back to operational systems.
Where this service sits in the model
What you receive
Runbook · data-pipelines5
- 01Pipeline architecture and data contracts
- 02Implemented, tested pipelines
- 03Orchestration and monitoring
- 04Lineage and documentation
- 05Operational ownership model
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