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Data Platforms & Analytics
Pipelines, warehouses and models that turn operational data into decisions.
Governed, tested and documented from source to dashboard.
01When to bring us in
The problem, stated plainly.
- P.01
Different teams report different numbers for the same metric.
- P.02
Analysts spend most of their time preparing data.
- P.03
Data needed for AI and reporting is locked in operational systems.
02What we deliver
Scope, in concrete terms.
- D.01
Data architecture: warehouse or lakehouse
- D.02
Ingestion pipelines from operational systems
- D.03
Tested, documented transformations
- D.04
Semantic layer and BI dashboards
- D.05
Governance, access control and lineage
03How we approach it
Four steps, one team throughout.
- 01
Define
Metrics, owners and sources agreed.
- 02
Ingest
Reliable pipelines with monitoring.
- 03
Model
Transformations tested like code.
- 04
Serve
Dashboards, APIs and datasets ready for AI.
04Typical stack
Typical, not mandatory. Your existing stack comes first.
BeginData Platforms & Analytics
Tell us where it hurts.
We will tell you what we would build.
A first call clarifies scope, risks and a sensible first increment. You leave with a plan either way.