Data Analytics
One number. One meaning.
KPI frameworks, semantic layers, and the governance that makes the definitions stick.
Every tool pulls from the same source. Every meeting gets shorter.
Data Analytics · live signal
What this engagement looks like by the numbers
0+
metrics defined
0
weeks avg · alignment
0
semantic layers
Problems we solve
If any of these sound familiar, we can help.
What we build
The deliverables.
KPI framework
North-star metrics, input metrics, and the tree between them.
Semantic layer
dbt metrics, Cube, or LookML — definitions as code.
Analytics engineering
Analysts who know dbt, git, and testing — not just SQL.
Governance
Definitions owned, documented, and debated in one place.
Engagement models
Three ways to work together.
01
Project-based
Stand up a KPI framework and semantic layer end-to-end.
Cadence
- Week 1-2Inventory + alignment
- Week 3-4Reconcile definitions
- Week 5-7Encode in dbt / semantic layer
- Week 8Rollout + training
- North-star metric definition
- Metric reconciliation across tools
- dbt semantic layer rollout
02
Fractional analytics
Embedded analytics engineer for teams without one.
Cadence
- DailyAd-hoc analysis
- WeeklyReporting packs
- MonthlyStakeholder sync
- QuarterlyFramework review
- Ad-hoc analysis
- Reporting packs
- Stakeholder communication
03
Advisory
Analytics architecture and team design.
Cadence
- On requestHiring panels
- MonthlyTooling / vendor evals
- QuarterlyGovernance review
- OngoingAsync architecture advice
- Hiring analytics engineers
- Tooling decisions
- Governance design
Tools we use
The toolbox.
SigmaSnowflakeBigQuery