We design, build and migrate Snowflake and dbt platforms — with testing and reconciliation built in, so the numbers hold up from day one.
Snowflake + dbt platforms with tests, documentation and ownership built in.
Move off legacy systems with parallel runs and reconciliation, so the new numbers are proven before cut-over.
Map inherited pipelines, add tests and lineage, and make failures easy to find and fix.
Shared metric definitions, Power BI reporting, and conversational analytics on top of a trusted model.
A 1:1 conversation about where your data stands and what is getting in the way.
We review sources, models and reports, and find where trust is breaking.
Short, hands-on cycles — each one delivering something your team can use.
Documentation, lineage and runbooks so your team owns it with confidence.
Short lessons on why data gets trusted — or ignored.
Operations made morning decisions from a dashboard that had silently stopped refreshing overnight. The numbers looked fine; they were simply yesterday’s.
Accuracy wasn’t enough without timeliness. Freshness checks on the key sources, plus a visible “data as of” stamp on every report, meant stale data announced itself.
Sales and finance both reported active customers, and both were correct by their own logic. Leadership just saw two numbers that never agreed.
This was a decision, not a bug. Getting one owner to choose the definition — then encoding and documenting it once in dbt — ended a debate no query could settle.
Warehouse costs climbed month after month, and the instinct was to restrict who could run queries — which would have undone the adoption the platform was built for.
The spend came from a few full-refresh models and oversized warehouses, not from users. Making those models incremental and right-sizing compute cut cost without cutting access.
Tell us where things stand today. You'll leave with a clear view of what's working, what isn't, and a practical first step.