Collect Shopify Data into Google BigQuery
Own your Shopify data in Google BigQuery with OWOX Data Marts. Collect orders, customers, products, and transaction data directly into BigQuery, control schema and refresh logic, and reuse the data across BI tools and AI Insights.
Shopify Endpoints
25 Shopify endpoints you can import. Each lands in its own table in your warehouse.
Abandoned Checkouts
Checkout sessions that did not complete — customer info, items, and pricing for recovery campaigns.
20 fieldsTime seriesArticle Metafields
Custom metadata attached to articles — namespace, key, value, and type.
9 fieldsArticles
Blog articles — title, author, publication status, and timestamps.
15 fieldsBlog Metafields
Custom metadata attached to blogs — namespace, key, value, and type.
9 fieldsBlogs
Blogs in the store — title, handle, and template settings.
6 fieldsCollection Metafields
Custom metadata attached to collections — namespace, key, value, and type.
9 fieldsCollections
Product collections — title, sort order, product count, and last updated.
10 fieldsCustomer Metafields
Custom metadata attached to customers — namespace, key, value, and type.
9 fieldsCustomers
Customer accounts — contact info, marketing consent, order history, and lifetime spend.
22 fieldsTime seriesDiscount Codes
Discount codes — type, status, usage limits, and validity window.
12 fieldsFulfillment Orders
Fulfillment orders — items to ship, assigned location, delivery method, and status.
11 fieldsInventory Items
Inventory items (SKUs) — tracking status, shipping requirements, and country of origin.
9 fieldsLocation Metafields
Custom metadata attached to locations — namespace, key, value, and type.
9 fieldsLocations
Physical and virtual store locations — activity status, fulfillment capabilities, and address.
19 fieldsOrder Metafields
Custom metadata attached to orders — namespace, key, value, and type.
9 fieldsOrders
Orders placed in the store — financial and fulfillment status, customer info, totals, and timestamps.
47 fieldsTime seriesPage Metafields
Custom metadata attached to pages — namespace, key, value, and type.
9 fieldsPages
Static store pages — title, handle, publication status, and timestamps.
10 fieldsProduct Metafields
Custom metadata attached to products — namespace, key, value, and type.
9 fieldsProduct Variant Metafields
Custom metadata attached to product variants — namespace, key, value, and type.
9 fieldsProduct Variants
Product variants — SKU, price, inventory quantity, and availability.
18 fieldsProducts
Products in the store catalog — vendor, type, status, inventory, and price range.
21 fieldsTime seriesShop
Store settings — domain, currency, timezone, and plan details.
20 fieldsShop Metafields
Custom metadata attached to the shop — namespace, key, value, and type.
9 fieldsTender Transactions
Payment tender transactions — amount, currency, order reference, and processing time.
7 fields
Step 1: Create a Google BigQuery Data Storage
Start by connecting your Google BigQuery project as a storage.
- Use your Google Cloud project and BigQuery dataset
- Authorize with a Google account or service account
- Keep full ownership of Shopify data in your warehouse
Step 2: Create Shopify Data Mart(s)
Create a new Data Mart and choose Connector as the definition type.
- Select Shopify as the data source
- Authorize access to your Shopify store by adding a Shop Domain and the Admin API Access Token
- Define which e-commerce entities you want to collect
Step 3: Select Shopify Database & Fields
Choose exactly which Shopify data should be collected.
- Select entities such as orders, order items, products, customers, and refunds
- Define the dataset and table where data will be stored
- Publish Shopify Data Mart once configuration is complete
Step 4: Run & Schedule Shopify Data Collection
Once published, control how and when Shopify data is imported.
- Run manually and select Backfill to load historical data
- Add a Connector run Trigger so Shopify data is collected on your schedule
- All runs are logged and visible in Run History
Step 5: Get more from your Shopify Analytics
Your Shopify data is now available in BigQuery.
- Build revenue, orders, and product performance reports
- Blend Shopify data with ad platforms, GA4, or CRM data
- Enable Shopify Analytics AI Insights delivered on a schedule to Slack, MS Teams or by Email
Every claim has a receipt.
Real things real customers said — each quote pinned to a specific claim, straight from the quotes database.
Nodari RizunFounder & CEO, Pürblack®“AI, by the nature of the models, will hallucinate. And because of that, you need something which will create guardrails to ensure that there are no hallucinations, that you can trust your data.”
Mark SimmonsCMO, Pürblack®“We had six or seven different channels and no single source of truth — it was almost impossible, a lot of guesswork.”
Nodari RizunFounder & CEO, Pürblack®“We regained time. And time is the one resource that never comes back.”
- 0.34.0Temporary BigQuery faults no longer fail the whole import
- 0.33.0Calculated Fields in the Output Schema
- 0.33.0Cheaper incremental imports into Google BigQuery
- 0.33.0Checkout and cart tokens for Shopify orders
- 0.32.0AI metadata generation for SQL data marts: no dataset-creation permission, and visible failures
Turn Shopify Data into Business Decisions
Schedule a quick walkthrough to see how OWOX Data Marts helps you collect Shopify data in Google BigQuery, reduce reporting complexity, and scale analytics with confidence.
Get Started Free- Internal OWOX data as of 2026-10-02
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