Case Study: Nutrafol saves 100+ hours per month on dbt code review with Datafold Data Diff
Key results
The challenge
Nutrafol, a direct-to-consumer hair-wellness company, ingested data from numerous sources, and unintended changes to data models introduced errors. Leadership sometimes discovered dashboard errors before the data team did, and the team lacked visibility into the downstream pipeline impact of code changes.
The solution
Nutrafol implemented Datafold's Data Diff platform with column-level lineage to validate code changes before they reached production and to surface the downstream impact of modifications during pull-request review.
“Data Diff is great for scaling the PR review process. It creates consistency across every data engineer.”
CDCallie DavisVice President of Customer Data & Insights, Nutrafol
The results, in context
Nutrafol's data team saves more than 100 hours per month through automated regression testing and a streamlined tech-spec process, and achieved 100% consistency across pull-request reviews. The team also cut its reaction time to data outages from weeks to under 24 hours.