Analytics & Dashboards
Executive-ready dashboards backed by a modeled warehouse.
From raw data to decision-ready dashboards — modeled with dbt, served through Looker Studio, Metabase, or Power BI.
Problems I solve
- Every team reports different numbers
- Dashboards nobody trusts
- Metrics that change definition silently
- No self-serve — every question needs a data person
What you get
- Semantic layer with versioned metric definitions
- Dbt models with tests + docs
- Role-based dashboards (exec / marketing / product)
- Self-serve exploration for power users
Use cases
Executive KPI dashboard
One page with revenue, retention, pipeline, and CAC — refreshed hourly.
Marketing performance
Blended ROAS, channel mix, CAC payback by cohort.
Product analytics
Activation, retention, feature adoption for PLG teams.
Ops & finance
Cash, runway, unit economics with drilldowns to raw transactions.
Examples I've shipped
SaaS exec dashboard
Outcome — Board pack auto-generated the day of the meeting.
E-comm marketing hub
Outcome — Team stopped exporting CSVs; decisions moved from weekly to daily.
How I work
- 1
Metric definition
Agree the exact SQL and grain for every headline number.
- 2
Model
Dbt models with tests, docs, and lineage.
- 3
Visualize
Role-based dashboards with clean IA.
- 4
Enable
Training + written definitions so metrics stop drifting.
Deliverables
- Modeled warehouse
- Role-based dashboards
- Metric definitions doc
- Training session
Benefits
- One version of the truth
- Faster, better decisions
- Self-serve for power users
Frequently asked questions
Do we need dbt?+
For anything beyond a handful of tables, yes — it's the cheapest way to keep metrics consistent and tested over time.