A warehouse your analysts trust is the whole point
A data warehouse earns its keep when two analysts run the same question and get the same number. DEV3LOPCOM, LLC, an Austin, Texas consultancy, designs and builds warehouses around that standard: clean dimensional models, governed metric definitions, pipelines that load on time, and documentation that explains why each table exists. We work across cloud warehouse platforms and SQL databases, and every engineer on the engagement is onshore.
We are platform-pragmatic. The right answer might be a cloud warehouse, a well-indexed Postgres instance, or restructuring what you already own. We recommend based on your query patterns, data volume, and team skills — not based on a reseller agreement, because we don’t have one.
How a warehousing engagement runs
We start with an assessment: where data comes from, how it is modeled today, which reports depend on which tables, and where numbers diverge. Then design — a target model with defined facts, dimensions, grain, and metric logic, plus the pipeline architecture to feed it. The build phase migrates incrementally: new models run alongside old ones until the numbers reconcile, so nobody has to trust a big-bang cutover. Handoff includes model documentation, load runbooks, and training so your team extends the warehouse without calling us for every new table.
The pipeline side of this work leans on our advanced ETL practice; if the surrounding data platform needs work too, see data engineering consulting.
Warehouse problems we fix
- Three versions of “revenue” that disagree because metric logic lives inside individual dashboards instead of the model.
- Slow BI performance caused by reporting tools querying raw operational tables.
- Warehouses that grew by accretion — hundreds of tables, no naming convention, nobody sure what is safe to drop.
- Loads that finish late or fail quietly, so Monday’s numbers are really Friday’s.
- Excel as the de facto warehouse, with all the version-control chaos that implies.
This is territory we know from client work. For Buxton we built GCP pipelines feeding an environment of more than 100 Tableau workbooks — see the Buxton case study. At Lever, rationalizing 282 SQL queries and 186 workbooks into a coherent modeled layer now saves roughly 22,000 hours per year (Lever writeup).
Why dev3lop
Our founder is a former Tableau Software Professional Services consultant, and it shows in how we model: warehouses are designed backward from the dashboards and decisions they serve, not forward from whatever the source system emits. That is also why warehousing engagements pair naturally with Tableau consulting when the reporting layer needs the same cleanup. Small senior team, direct communication, documentation as a deliverable rather than an afterthought.
Scope your warehouse project
Whether you are starting from spreadsheets or modernizing a decade-old warehouse, the first step is the same: a short assessment that maps what exists and what it should become. Contact us and tell us what your reporting stack looks like today.