Connect Shopify with Microsoft Power BI to consolidate store, ad, CRM, ERP, and GA4 data, then model it into reliable eCommerce KPI dashboards your team can act on.
• Shopify data (orders, customers, products, refunds, and payouts) is extracted via Shopify APIs and loaded into a centralized warehouse or Power BI dataset for analytics-ready storage.
• Incremental sync logic pulls deltas based on updated timestamps and IDs, with periodic backfills handling late updates, cancellations, and refund adjustments.
• Marketing, CRM, ERP, and web analytics sources are ingested in parallel, then conformed to shared dimensions (date, channel, campaign, customer, product, and location).
• Identity mapping links records across systems using keys such as order number, email, customer ID, SKU, and UTM parameters, with exceptions logged for review.
• Data modeling applies star-schema structures and calculated measures for common eCommerce KPIs (revenue, gross margin, AOV, CAC, ROAS, LTV, and cohort retention).
• Refresh schedules and monitoring capture run status, row counts, and validation checks, routing failures to alerts and keeping audit trails for changes.
.png)
We extract Shopify orders, customers, and products into a warehouse (often BigQuery or Snowflake), model the dataset, then publish curated tables to Power BI for reporting.
Typical models cover revenue, refunds, discounts, taxes, COGS, gross margin, AOV, LTV, and product, channel, cohort, and time dimensions, if those sources are available.
Yes, we build a single reporting layer that joins Shopify commerce data with marketing, analytics, ERP, and CRM sources, so KPIs match across teams and reports.
We standardize store identifiers, currency conversion logic, and attribution rules in the data model, then expose both local and normalized views in Power BI.
scandiweb has delivered 575+ eCommerce BI dashboards and has 60+ certified GA4 and Adobe Analytics experts to validate tracking and KPI definitions end to end.









