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Join marketing, finance, CRM, and product data inside the same warehouse.
Metrics availables
Dimensions availables
Enter the Azure SQL server host, database, and login details. Catchr verifies the destination before any marketing data is exported.
Choose the fields, initial history, partition field, and recurring schedule for the job. Catchr refreshes the configured import window in your AzureSQL table.
This example summarizes revenue, orders, units sold, and average order value by sales channel.
Open the dedicated route for each platform. Its field catalog, reporting grain, historical constraints, and warehouse use cases should be specific to that source.
Answers about AzureSQL setup, available source data, schedules, table updates, and SQL use cases.
Register WooCommerce, save the Azure SQL connection details, and pair both systems in a datastream. The associated job previews and writes the selected columns to "orders".
Select concrete WooCommerce fields such as Shop Total Customers, Shop Total Coupons Used, Shop Total Items Purchased, and Day of the month. You can rename the chosen columns, preview the result, and write them to Azure SQL tables such as stores, customers, and products.
The "orders" job can begin with a historical WooCommerce fetch and continue on a recurring schedule. Available history and frequency depend on the source API and your plan.
Select a valid date field when configuring the WooCommerce job for "orders". Catchr deletes and rewrites the scheduled window, limiting duplicate rows across overlapping runs.
With WooCommerce data, an Azure SQL query can summarize revenue, orders, units sold, and average order value by sales channel. Turn Shop Total Customers and Shop Total Coupons Used into a stable Azure SQL view that analysts and reporting tools can query repeatedly.
Yes. Connect an existing Azure SQL database first. The Catchr job creates and populates the destination table you configure inside that database.
Yes. Create a separate datastream and job for each source, write each export to its own table, then combine the data downstream with SQL, views, or your BI tool.
Our teams is always here to responds to any question you could have about our data connector.