Growth has a shape.
We build idempotent pipelines, a governed warehouse and tested forecasts, so every metric has lineage, a freshness SLA and one definition.
§ 01
Premise
Most organisations are not short of data. They are short of a contract: one versioned definition per metric, with lineage to source and a freshness SLA. We build that contract, and the pipelines that enforce it.
§ 02
Method
Three layers, shipped in dependency order.
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2.1
Ingest
CDC and batch ingestion from every source, landed idempotently and modelled in the warehouse, so analysts query marts, not raw tables.
- CDC & batch ELT
- Dimensional marts
- Freshness & schema tests
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2.2
Forecast
Forecasts and anomaly detection, backtested on your history and shipped with prediction intervals. A point estimate is an opinion.
- Backtested demand forecasts
- Metric anomaly alerts
- Scenario planning models
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2.3
Serve
A semantic layer so every dashboard resolves to one governed definition, and reporting that surfaces the one metric that moved.
- Semantic layer & metric store
- Executive dashboards
- Scheduled board pack
§ 03
Practice
Reference engagement, drawn to scale.
§ 04
SLAs
SLAs we hold every engagement to.
- Freshness SLA
- < 15min
- P95 target, source commit to dashboard refresh.
- Metric contracts
- 1per metric
- One versioned definition, owner and lineage graph.
- Test coverage
- 100%
- No model merges without schema, null and freshness tests.
- Ownership
- Yours
- Code, IaC and state live in your cloud accounts.
§ 05
Contact