“SourceMedium has future-proofed our data infrastructure. Their comprehensive solution not only supports our current needs but is also scalable as we grow. With their managed BigQuery instance, we have full control over our data, creating custom metrics and insights rapidly. This has empowered our team to answer complex business questions and focus on strategic growth initiatives.”
A real warehouse. Yours to query, extend, and keep.
Your ecommerce data lives in a managed BigQuery instance with dedicated compute reserved for your brand — not a vendor's database you're renting. BI and transformations don't fight for resources. Any tool that supports BigQuery connects natively. If you ever leave, it comes with you.
Integrated AI-to-BI stack on Google Cloud
Why we chose BigQuery.
Not a default. A deliberate choice.
Zero-maintenance, serverless scaling
Eliminate the overhead of warehouse resizing and credit management. BigQuery's serverless architecture automatically allocates compute to match query demand, ensuring performance without paying for idle capacity. No infrastructure tuning required.
Direct-path first party data ingestion
Leverage Google's native, high-bandwidth data transfers for GA4 and Google Ads. Bypass third-party ELT connectors for your highest-volume datasets, reducing latency, failure points, and ingestion costs.
Decoupled storage and compute economics
Store petabytes of historical data at archival rates while maintaining millisecond-access for queries. Decoupled architecture means you never pay for compute resources just to hold data, making multi-year longitudinal analysis economically viable.
Zero-license, democratized BI
Remove seat-based licensing friction. Looker Studio connects natively to BigQuery's BI Engine for sub-second dashboards at no additional cost. Empower every stakeholder with data access without managing complex enterprise BI contracts.
Unified AI and Analytics ecosystem
Operationalize AI where your data lives. Access Vertex AI and Gemini models directly via SQL within BigQuery. No data movement, no separate ML infrastructure—just a unified layer for descriptive analytics and predictive intelligence.
What your team can actually do with it.
The BigQuery advantage, made concrete for every role.
Data teams
- Run custom SQL on your own data — no export workarounds, no API limits
- Build dbt models on a documented, stable schema
- Connect Tableau, Python, Hex, Mode, or any BI tool natively
- Run custom transformations with included compute
- Use the schema as a foundation — extend it without breaking it
Growth teams
- Pre-built dashboards read directly from BigQuery — one source of truth
- AI Analyst answers questions in Slack with SQL you can verify in BigQuery
- Attribution, LTV, cohort analysis — all queryable, all auditable
- No new interface to learn if you just use dashboards + Slack
Executives
- Numbers reconcile back to Shopify and your ad platforms — no more "which revenue is right?"
- Board-ready reporting from the same warehouse your data team queries
- If you ever hire a data team or bring in an analyst, they inherit a documented, governed foundation — not a mess
Agencies + consultants
- Plug into your existing workflow — Hex, Mode, dbt, Tableau, any BigQuery-compatible tool
- No data export rituals, no vendor UI lock-in
- Serve multiple clients from a consistent, documented schema
- Build custom analyses without learning a proprietary interface
Trust layer
A schema you can build on.
The reason data teams prefer working with us.
We spent six months on naming conventions. Tables, columns, and definitions designed to be stable and supported for years — not thrown together by a contractor. When we evolve the schema, we do it carefully, with backward compatibility in mind.
Put dbt on top — it won't break. Onboard a new analyst — they can read our data transformation documentation. Build a custom model — you know the foundation won't shift under you.
2,500+
daily quality checks
180+
metric catalog
Consistent
Best-practice naming
Native
dbt-compatible
Example: orders table
| Column | Type |
|---|---|
| sm_order_key | STRING |
| order_processed_at | TIMESTAMP |
| order_net_revenue | FLOAT |
| sm_channel | STRING |
| sm_order_type | STRING |
| sm_customer_key | STRING |
| is_subscription_order | BOOLEAN |
| is_order_sm_valid | BOOLEAN |
Extensibility
Your BigQuery warehouse isn't limited to ecommerce.
Because your data lives in BigQuery — not a proprietary vendor system — you can centralize anything. Finance data, ops data, custom sources, third-party APIs. Standard BigQuery storage — no additional vendor fees for bringing in more data.
SourceMedium manages the ecommerce foundation. Your team extends the warehouse however you need.
Costco + grocery store data
Catalina Crunch integrated retail POS data alongside their ecommerce data — built a real-time P&L dashboard in 3 weeks.
Custom fulfillment data
CPAP set up webhooks to pull fulfillment-date revenue recognition into BigQuery for finance-grade reporting.
Third-party data via Google Sheets
Brands that need non-automated data (SPINS, wholesale, marketplace) upload via Google Sheets on a cadence, cast to the schema, and it becomes part of the same governed foundation.
If you leave, do you keep everything?
- Full data export & transfer
- Custom SQL queries & models
- Looker Studio dashboards
- Schema & metric documentation
Yes. You keep your data.
Your data, your control
Built to stay. Free to leave.
Our internal dbt models and SQL transformation logic remain SourceMedium IP. Your data, schema, and any custom models you built are yours to keep—export them or transfer the BigQuery tables to your own project.
Trusted by fast-growing e-commerce brands
Testimonials
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