One warehouse joining ads, orders, CRM and ERP,
with the cost logic actually right
A warehouse with wrong joins is worse than no warehouse, because wrong numbers get trusted. We build the joins and cost logic correctly first, then dashboards on top that your team actually opens, not a report that gets emailed and ignored.
Why the joins matter more than the charts
A data warehouse and BI product joins every source your business actually runs on: ad platforms, CRM, orders, an ERP, into one place. Cost and revenue logic reflects how your business genuinely makes money. Dashboards on top surface that for people who actually open them.
This fits any team currently stitching numbers together by hand, in spreadsheets, from several disconnected tools. It is not worth building for a single data source already well served by that platform’s own reporting. The value shows up once you need to see across sources, not inside just one.
What is inside
Connectors pull from each real source on a schedule. No manual export, no copy-pasting into a spreadsheet that goes stale within a day. The core work is cost and revenue logic that matches your actual business. True cost of goods from an ERP. Platform fees correctly subtracted. Currency and timezone handled consistently. This is where most warehouses quietly go wrong.
Dashboards sit directly on top of the warehouse, built around the questions your team actually asks, not a generic template of charts nobody reads. Data quality checks run on every refresh, catching a broken connector or an unexpected schema change before it produces numbers that look fine but are not.
How we build it
We map your real sources first, and just as critically, your real cost structure. A warehouse that gets cost of goods or fee structures wrong produces confidently wrong profit numbers, which are worse than no numbers at all. Connectors get built and validated against known-correct historical numbers before anything reaches a dashboard.
We launch dashboards around the specific questions your team currently answers manually. That proves the warehouse replaces that manual work exactly, before we expand to additional views. Data quality checks get built and tested with deliberately broken inputs: a connector returning nothing, a schema change. A failure gets caught immediately, rather than discovered weeks later in a wrong number someone already acted on.
What to watch
The real risk in any warehouse is cost or revenue logic that is quietly wrong but looks authoritative. That is more dangerous than an obvious gap, because nobody double-checks a number that looks plausible. That is why cost logic gets validated against figures your team already knows are correct, before any dashboard ships.
Source API changes are the other recurring risk. A platform updates its reporting API, and a connector silently returns incomplete data. That is exactly what the data quality checks are built to catch. Expect periodic connector maintenance as source platforms evolve. Budget a little ongoing attention for this, not a one-time build.
Timeline and price
| Option | Price | What it covers | Timeline |
|---|---|---|---|
| MVP | from $2,500 | Two to three sources joined, basic dashboards, scheduled refresh | 5 to 6 weeks |
| Production | from $7,000 | Full source set including ERP cost data, data quality checks, documented schema | 7 to 9 weeks |
| Full control (handover-ready) | from $8,000 | Everything in Production, plus a full handover package: architecture docs, test suite, admin access audit, and a walkthrough so your own team or another vendor can run it without us | 9 to 10 weeks |
Running cost on top of the build is usually $25 to $90 a month in hosting and refresh compute, depending on source count and data volume.
What you own at the end
You own the warehouse, the connectors, the transformation logic and the dashboards, running on your own infrastructure with no recurring BI license required. Full documentation of every table and join means the warehouse is never a black box to whoever inherits it.
Related
Pairs with ETL and integrations hub for the connector layer underneath, and AI business data analyst for a chat interface on top of the same warehouse. See the analytics service page for audits and the full range of analytics work we do. Real builds: the analytics hub case study and the factory ERP recovery case study, whose recovered data became the warehouse this kind of product runs on. Still exporting numbers from four tools into one spreadsheet every week? Get in touch.
FAQ
How much does a data warehouse cost?
From $2,500 for joining two or three sources, say ads and orders, with basic dashboards. A full warehouse joining ads, CRM, orders and ERP with correct cost logic runs $6,000 to $12,000.
How long does it take?
Five to six weeks for a smaller join of two or three sources. A full warehouse with ERP cost data and multiple reporting views takes eight to ten weeks. Getting the cost logic right takes real back-and-forth with your team.
What is the stack?
PostgreSQL for the warehouse itself, Python for connectors and scheduled refresh jobs. A dashboard layer, usually Next.js or a BI tool you already use, reads directly from the warehouse rather than a stale export.
Who owns the warehouse?
You do. The database, the connectors, the transformation logic and the dashboards run on your own infrastructure. There is no recurring per-seat BI license required unless you choose to layer one on top.
What happens if a source connector breaks?
Data quality checks catch a broken connector, a feed that stopped updating, a schema change upstream. They catch it before bad or missing numbers quietly spread into dashboards your team trusts.