Productized — Fixed scope — Fixed price
Production data lake.
Weeks, not quarters.
ADF + Databricks + dbt + a custom app on top. Most consultancies hand you a dashboard. We ship a working interface your team or customers will actually use. Our last build went live in 14 days — below is the actual playbook it ran on.
The stack
Boring, proven, fast.
We chose this stack because it ships in days, not months. Every piece is industry-standard and well-staffed. No exotic dependencies. No vendor lock-in beyond what your cloud already has.
- 01
Azure Data Factory
Ingestion + orchestration
- 02
Databricks
Lakehouse + compute
- 03
dbt
Transformations + tests
- 04
Custom app (Next.js)
What your team and customers actually use
The playbook — Week 1
Pipelines and the bronze layer.
How the last build ran. By Friday of week 1, real production data was flowing into Databricks — visible, queryable, real.
Day 1–2
Discovery + access
Source-system kickoff, Azure tenant access, credential exchange, scope confirmation. By end of day 2 we have the keys and a target schema sketch.
Day 3–4
ADF pipelines + landing zone
Ingestion pipelines for every source, scheduled or event-driven. Bronze landing in ADLS Gen2, partitioned and cataloged.
Day 5
Databricks workspace + bronze
Workspace provisioned, cluster sized, bronze layer materialized. Initial sanity dashboards so we can see real data flowing.
The playbook — Week 2
Models, the app, and handoff.
The transforms get clean and the app gets built. Day 14 is the handoff — you walk away with a running system and the keys.
Day 6–8
Silver + gold dbt models
dbt project with sources, staging, marts, and tests. Gold tables that match how the business actually thinks. Documentation auto-generated from dbt.
Day 9–10
Custom app build
Next.js app that reads from the gold layer — the interface your team or customers actually use. Auth, role-based views, the screens that matter most.
Day 11–12
Testing + handoff
End-to-end tests, runbook, Loom walkthrough of the whole stack, repo handoff to your engineering team (or our retainer).
Day 13–14
Iteration buffer
Two days to absorb whatever showed up — schema surprises, business-logic edge cases, dashboard requests. Built into the price; not a change order.
The differentiator
Why a custom app,
not a dashboard.
BI tools optimize for analysts who already know the question. Custom apps optimize for the people who don’t — your sales reps, ops leads, customers, frontline staff.
A dashboard answers what happened. An app answers what should I do, and how do I do it. One produces insight. The other produces action.
Building the app on top of the data lake is also why this ships in weeks instead of months — when you control the transforms and the interface, you can change a column definition and ship a new screen in the same afternoon.
What’s included
- Azure Data Factory pipelines (up to 8 sources)
- Databricks workspace + bronze/silver/gold layers
- dbt project with tests, docs, and CI
- Custom Next.js app deployed to Vercel
- Documentation + Loom walkthroughs
- 30 days of iteration support post-handoff
What’s not
- New source-system contracts (you bring API keys; we wire them up)
- ML model training (separate engagement)
- Long-term ops + on-call (transitions to your team or our retainer)
- Multi-tenant productization or white-label work
What we need from you
- Admin access to the systems in scope (or a named person who unblocks same-day)
- Credentials for every source system, before the clock starts
- One SME for domain questions (~45 min/day)
- One decision-maker available for sign-off
FAQ
The questions you should be asking.
- Can you do AWS or Snowflake instead?
- Yes. The base scope assumes Azure + Databricks because that stack is fast for us, but we adapt to your existing cloud. AWS + Snowflake + dbt is a clean swap; AWS + Redshift + dbt also works.
- Who owns the code?
- You do. We hand off the repo, the Azure resources, and a runbook on day 14. No lock-in, no ongoing license fees from us.
- What if our sources are messier than expected?
- We flag it on day 1 — if the scope grows, you hear it from us first, with a number, before we start. We don't quietly burn the iteration buffer and then ask for more. No surprise invoices.
- Why a custom app instead of Power BI or Tableau?
- BI tools are for analysts. A custom app is for the people who actually act on the data — sales, ops, customers. A dashboard answers “what happened?” An app answers “what should I do, and how do I do it?” That's the difference between insight and execution.
- Can we start before signing the SOW?
- Yes. We can run a paid 1-week discovery that credits toward the build. Useful when scope is genuinely uncertain.
- What happens after handoff?
- Three options: (1) take the keys and run it yourselves, (2) a monthly Run plan — we keep it healthy, updated, and supported, (3) phase 2 build (more sources, ML, customer-facing scale). Training for your team is available as a separate block.
Pricing
Agency execution.
Studio pricing.
We deliver what a traditional consulting agency would scope as a multi-month, six-figure engagement — in weeks, fixed scope, on a studio’s overhead. The structure is different, not the rigor. Send us your sources and constraints; we’ll send a fixed number within two business days of a 30-minute scoping call.
Reply within two business days