06:00 UTC













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.
Register Tripadvisor Review, save the Azure SQL connection details, and pair both systems in a datastream. The associated job previews and writes the selected columns to "ratings".
Select concrete Tripadvisor Review fields such as Average Rating, Cleanliness Rating, Location Rating, 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.
The "ratings" job can begin with a historical Tripadvisor Review 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 Tripadvisor Review job for "ratings". Catchr deletes and rewrites the scheduled window, limiting duplicate rows across overlapping runs.
With Tripadvisor Review data, an Azure SQL query can summarize review volume and average rating by location over the last 30 days. Turn Average Rating and Cleanliness Rating 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.