Datablast for Analytics Engineers
Model once. Every team gets the same answer.
A governed knowledge layer turns your models into shared business definitions. Flare answers questions using your metrics — so self-serve stops meaning "everyone computes their own revenue".
The problem
Sound familiar?
Metric drift is constant
Three dashboards, three revenue definitions. You fix one; two more appear in someone's spreadsheet.
Documentation dies on contact
The wiki is stale the day after you write it. New joiners learn definitions by asking you.
Self-serve tools bypass your models
BI tools let anyone join raw tables — and they do, producing numbers that contradict your carefully built marts.
What teams build
Analytics Engineers use cases on Datablast
Governed metric definitions
Define revenue, active users, and churn once. Dashboards, summaries, and Flare all speak the same language.
Flare that respects your models
Plain-language questions are answered from governed definitions — not from creative raw-table joins.
Faster model development
Flare drafts new models and modifications against your existing structure; you review and refine.
Impact-aware changes
Lineage shows every dashboard and workflow a model change touches, before you merge it.
Living documentation
Definitions live next to the models and surface wherever the metric appears — always current.
One
definition per metric, everywhere
Fewer
"why do these numbers differ" threads
Faster
modeling with Flare-drafted changes
Works with your stack
Ready to build a data foundation your whole team can trust?
See how Datablast and Flare work together — in a walkthrough built around your stack.