Staff augmentation for fast analytics
How WholesomeCo's Director of Analytics partnered with Systematik to augment their team and migrate their data transformations to dbt.
“Our goal was to consult with experts on how to implement dbt, and build a robust, modern data architecture, and they do that really well.”
Mitchell MoodyDirector of Analytics, WholesomeCo
A data pipeline that couldn't scale
WholesomeCo's analytics ran on BigQuery scheduled views — with no version control, no cost controls and no real data-quality monitoring. As data demands grew, that setup led to rising costs, inconsistencies and errors. They needed to augment their team and move to a modern, maintainable transformation layer.
Migrating transformations from BigQuery scheduled views to dbt without disruption.
Bringing version control and testing to a pipeline that had neither.
Reining in query costs and removing redundant logic.
Standardizing metric definitions so every department agreed on the numbers.
We embedded with WholesomeCo's analytics team as an extension of their staff, rebuilding their transformation layer in dbt — version-controlled, tested and documented — while streamlining queries to cut cost and improve data quality.
Staff augmentation
We integrated directly with their Director of Analytics' team, bringing dbt and data-engineering expertise to accelerate the migration.
Migration to dbt
We moved their BigQuery scheduled views into a modular, version-controlled dbt project with automated tests.
Cost & quality
We streamlined queries and removed redundancies to cut cost, and added data-quality monitoring to catch issues early.
Documentation & metrics
We documented models and standardized metric definitions so every team shares one understanding of the numbers.
WholesomeCo came away with a faster, more scalable pipeline — version-controlled, tested and documented — with lower query costs, fewer errors and metric definitions the whole company trusts.
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