We audit every model, rewrite slow ones with incremental + microbatch strategies, prune unused exposures, and turn 4-hour runs into 40-minute runs.
Slow dbt runs are rarely about Snowflake or BigQuery — they're about repo shape. Wide select-stars, materializations chosen by habit, missing incremental keys, stale exposures fan-out into a graph that runs for hours. We do the deep work most teams don't have the time for.
A practitioner’s plan to migrate from Redshift to Snowflake with minimal risk: inventory, data transfer and CDC, SQL/dbt gaps, security, BI cutover, reconciliation, and decommissioning.
A concrete migration plan to implement the dbt Semantic Layer without rewriting every metric: inventory, model entities and grains, define metrics, validate, secure, integrate, and roll out in stages.
A practitioner’s playbook to run a data quality audit across your highest-impact data products—and leave with a prioritized 30/60/90‑day remediation plan.
We maintain a small client roster on purpose. If we're the wrong fit, we'll say so — and usually we know somebody who isn't.