Data Analysis
Decision-grade analytics, modeling, and dashboards
Modern data stacks for B2B operators — pipelines you can audit, dashboards your team actually uses, models that survive the next reorg.
What we actually do
We build the layer between your operational systems and the decisions your leadership team needs to make. That's a data stack — ingest, transform, warehouse, model, serve — sized to your business and built so your team can own it. We're not in the business of producing weekly PDFs.
Every engagement starts with the same question: which decisions does this need to make better? Once the answer is concrete, the rest of the work has a north star — what to pipe in, what to model, how to surface it, and how to know it's working.
The stack we default to
Warehouse choice depends on volume and budget — Postgres scales further than most teams realize, BigQuery wins on cost at scale, Snowflake when you need the ecosystem. dbt is non-negotiable: your transformations live in version control, get tested, and are reviewable like any other code.
How a typical engagement runs
Weeks 1–3 · Foundation
Source-system audit, target metrics defined with the people who will actually use them, warehouse set up, first ingestion pipelines live. You see real data in a dashboard by end of week three.
Weeks 4–10 · Modeling + delivery
dbt models for the metrics that matter, dashboards in your tool of choice, alerting on the metrics that should never silently move. We pair with someone on your team the whole way — by the end they own the stack.
What you actually get
A warehouse you control. Pipelines that pull from the systems your business actually runs on. A dbt project that documents itself. Dashboards your team uses for real decisions — not for status reports nobody reads. And a team on your side that can extend the models when the business changes, which it will.
The proof: Nimbus Logistics replaced overnight Excel reports with real-time dashboards driving same-day dispatch decisions across 14 distribution centers. Reports that used to land at 7 a.m. tomorrow now land at 7 a.m. today.
Where Data Analysis shipped.
ManufacturingFrom 14-day close to 2-day close: ERP for Acme Manufacturing
Replaced 6 disconnected systems with a unified Odoo deployment, cutting month-end close from 14 days to 2.
LogisticsReal-time analytics for Nimbus Logistics
From overnight Excel reports to real-time dashboards that drive same-day dispatch decisions across 14 distribution centers.
Three services.
One conversation.
Tell us where the friction is. We'll come back with a plan, not a deck.