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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 review volume and average rating by location over the last 30 days.
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.
Create the Airbnb Review source, then register Azure SQL with its server host, database name, username, and password. Link both through a datastream and target the "review sources" table in the job.
Select concrete Airbnb Review fields such as Rating, Review Count, and Day of the year. You can rename the chosen columns, preview the result, and write them to Azure SQL tables such as review sources, locations, and reviews.
Configure the initial Airbnb Review period separately from the recurring schedule for "review sources". The source API determines how much history is available.
Choose an eligible date field as the partition for Airbnb Review. Catchr can then replace the matching period in "review sources"; without it, later runs append rows and may create duplicates.
With Airbnb Review data, an Azure SQL query can summarize review volume and average rating by location over the last 30 days. Use Rating and Review Count in an Azure SQL view to create a reusable reporting layer for client analysis.
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.