We use Dataform in Google Cloud to transform scattered marketing data into clean, structured models — giving every team a single source of truth.
Raw marketing data is a mess — events arrive in different formats, platforms define the same metric in different ways, and without a solid modeling layer in between, every team quietly builds their own version of "the truth." That's how you end up with three dashboards and zero alignment.
Data modeling solves this by transforming raw data into clean, documented, and version-controlled datasets. We use Dataform in Google Cloud (BigQuery) to build transformation pipelines that turn your raw event data into business-ready models ready to power your dashboards and analysis.
We start by understanding your data sources and business definitions — what does a "conversion" actually mean for your business? What's a "session"? These definitions drive the model design.
From there, we build transformation layers in Dataform: staging models that clean and standardize raw data, intermediate models that join and enrich, and mart models that serve your analytics and dashboards. Everything is tested, documented, and deployed through CI/CD — so your data pipeline is as reliable as your product pipeline.
Data modeling transforms raw marketing data (events, clicks, transactions) into clean, structured datasets with consistent definitions. Instead of every team interpreting raw data differently, you get one reliable source of truth.
Dataform (now part of Google Cloud) lets us write SQL-based transformations that are version-controlled, testable, and documented. BigQuery handles massive datasets without performance issues. Together they give you an enterprise-grade data pipeline without enterprise complexity.
Tell us about your goals and we'll figure out the right approach — no commitment required.