RA Warehouse for dbt

Leverage the power of an open-source dbt package using Stitch, Segment, Fivetran, Google BigQuery and Snowflake DB.


RA Data Warehouse for dbt is a set of data models, data transformations and design patterns we use to build data warehouse layers for client analytics projects. It combines modern, modular data stacks and our enterprise data warehouse project experience. Our framework toolkits are actively used by clients from industries such as tech startups, mobile apps, retail and more


We connect pre-built SaaS data source modules to common routine sets to combine, deduplicate and integrate datasets. We deliver faster projects more efficiently at lower costs for clients


We produce higher quality toolkits, as we’ve already ironed-out all the bugs and refined the code over multiple engagements


We create more value for clients by spending our time delivering analytics insights, rather than spending re-inventing the wheel

Deep Dive


Here's a closer look at how we get real value from our dbt set up. Head to GitHub for a closer look at our template.

Multi-functional set-up

Our framework provides integrated, best-practice datasets KPIs for our packaged Marketing Attribution, Product Analytics, Operational Analytics.

Community focused

For the dbt community, our warehouse is available in a public Github repo for anyone to clone, fork or contribute new functionality for interested analytics engineers.

Pre-built models and support

We have data source models for popular SaaS applications (Hubspot, Xero, Facebook Ads, Segment etc.) and support for Stitch, Fivetran and Segment data pipeline services.

Warehouse compatibility

RA Warehouse for dbt is compatible with Google BigQuery and Snowflake Data Warehouse.

Smart Logic

Data transformation and integration logic that combines multiple sources, deduplicates and creates single contact and company records.


Utilities for data profiling, ETL run logging and analysis. Simple configuration via settings in a single configuration file (dbt_project.yml).

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