From source systems to executive-ready reporting.
We build the full Databricks solution—from pipelines and Delta tables to semantic models and dashboards—so every metric is trusted.
Four stages, one governed line to the dashboard
Lakeflow pipelines land and shape data with tests between layers — bad records quarantine instead of flowing downstream.
Business-ready Delta tables with documented definitions — one version of each metric, owned and discoverable.
Serverless SQL sized for BI concurrency — fast dashboards without a cluster someone forgets to switch off.
Power BI or Databricks dashboards on the gold layer — certified, validated against legacy numbers before release.
The unglamorous parts we insist on
Unity Catalog underneath everything
Permissions, lineage, and documentation in one place from the first table. Retrofitting governance onto a grown lakehouse is the expensive way around.
Semantic definitions, written once
Metrics defined in the gold layer and the BI model deliberately — not re-derived in every dashboard until three versions of margin circulate.
Cost designed in
Serverless where it fits, auto-stop everywhere, and job-level cost visibility. Databricks bills for compute; the architecture decides how much you use.
Your engineers in the build
Pipelines are code your team reviews and owns from day one. The second subject area should ship without us — that's the design goal.
Bring your data platform goals. We'll map the path.
A strategy call to discuss your analytics priorities, your current architecture, and the best approach to building on Databricks.