Boutique data, analytics, ML and AI
Founder-led delivery from Lisbon
Pipelines, models, and production AI
English-first · EU-based studio
Start a project — we ship
Decision-grade data, not dashboards for their own sake
Boutique data, analytics, ML and AI
Founder-led delivery from Lisbon
Pipelines, models, and production AI
English-first · EU-based studio
Start a project — we ship
Decision-grade data, not dashboards for their own sake
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Analytics

Reasoning for decisions

From metric design to executive packs. DatabyPassion builds analytics that operators actually use — lineage included.

Start an analytics project
End-to-end

How we work across the value chain

Click any stage to see how DatabyPassion delivers that part of the work.

01

Map the decision landscape

We identify the decisions that move the P&L and the metrics that should govern them — with the people who make the calls today.

Decision inventory

Which calls are slow, disputed, or gut-feel.

Source map

Where the numbers really live.

How it lands

Engagements in the studio

Placeholder workflows — replace with named work when you are ready.

Workflow: Executive pack

Placeholder — wealth / finance operator

A placeholder engagement: one pack, one grain, one owner. Replace with a named case when ready.

Conflicting KPI definitions
Manual month-end assembly
No lineage when numbers are challenged
Cycle time (placeholder)
Manual hours (placeholder)
Workflow: Experimentation

Placeholder — product / growth team

Design, power, and readout of experiments on a shared metric layer.

Tests without a north-star metric
Readouts that cannot be reproduced
Tests / quarter (placeholder)
Decision lag (placeholder)
Proof points

Impact you can measure

Placeholder metrics until you confirm real numbers.

Placeholder · time-to-pack
Placeholder · metric disputes
Placeholder · self-serve adoption
Placeholder · coverage

See this practice on your stack

Start a project and we will map the first 90 days.