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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.
Connect TikTok Shop and add Azure SQL as the stored destination. Create a datastream, then save a job that sends the required records to the "product variants" table.
Select concrete TikTok Shop fields such as Payment Buyer Service Fee, Payment Handling Fee, Payment Item Insurance Fee, 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.
Choose how far back the first TikTok Shop load should go and how much recent data each "product variants" run should refresh. Catchr splits large backfills into smaller intervals.
For recurring TikTok Shop loads, assign an eligible partition field to "product variants". Otherwise Catchr cannot match the refresh window and will append the returned records.
With TikTok Shop data, an Azure SQL query can summarize revenue, orders, units sold, and average order value by sales channel. Join Payment Buyer Service Fee and Payment Handling Fee with shared account or date keys to build a reusable performance model in Azure SQL.
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.