Connect HoorayHR to BigQuery
Send HoorayHR users, sick leaves, time offs and 1 more data type to BigQuery on a schedule. Refresh as often as every 15 minutes.
BigQuery
dataset hoorayhr
userssick_leavestime_offsleave_types
How to connect HoorayHR and BigQuery
4 steps. You can preview the HoorayHR data in Coupler.io before anything reaches BigQuery.
Step 1 of 4
Connect HoorayHR
Enter your HoorayHR username and password. You only do this once per account.
Step 2 of 4
Choose what to export
Pick the HoorayHR data you want in BigQuery.
Step 3 of 4
Connect BigQuery
Upload the JSON key file from your Google Cloud service account, then enter the dataset and table for the HoorayHR data.
Step 4 of 4
Choose a write mode and schedule
Every run either replaces or appends the data in BigQuery. Run it as often as every 15 minutes.
Each run overwrites users with fresh HoorayHR data.
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4 data types, including Users, Sick leaves, Time offs and Leave types.
With your HoorayHR username and password, entered once when you add the connection.
Yes. If the table doesn't exist in the dataset you choose, Coupler.io creates it on the first run and fills it with HoorayHR data.
Refresh the source field list in Coupler.io and select the new column. If you define the BigQuery table schema manually, add the column there too.
On a schedule you choose, from monthly down to every 15 minutes, depending on your Coupler.io plan.
Yes. Add more sources to the same data flow, for example Clockify or Harvest, and join or append them before the data reaches BigQuery.
