Connect My Hours to BigQuery
Send My Hours projects, users, time logs and 2 more data types to BigQuery on a schedule. Filter by date. Refresh as often as every 15 minutes.
BigQuery
dataset my_hours
projectsuserstime_logstagsclients
How to connect My Hours and BigQuery
4 steps. You can preview the My Hours data in Coupler.io before anything reaches BigQuery.
Step 1 of 4
Connect My Hours
Enter your My Hours API key. You only do this once per account.
Step 2 of 4
Choose what to export
Pick the My Hours 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 My Hours 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 projects with fresh My Hours data.
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Build your My Hours integrations with these destinations
Get the most of My Hours to BigQuery integration
Gather data
Understand data
Automate data
Act on data
5 data types, including Projects, Users, Time logs, Tags and Clients.
With your My Hours API key, entered once when you add the connection.
Yes. Set the start date to cover the period you need.
Yes. If the table doesn't exist in the dataset you choose, Coupler.io creates it on the first run and fills it with My Hours 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.
