Clockify to Google BigQuery

Automatically Export & Sync Clockify Data to Google BigQuery

Clockify
a black arrow pointing to the right
Google BigQuery
Full data sets
No instructions needed
No code
No complicated flow charts
No triggers
Set up in under 3 minutes
Flat pricing starting at $19 /month

Data sets

CustomFields
Projects-All
Projects+Tasks-All
Pre-blended combo set TASKS
Tags-All
Tasks-All by Project
Filterable
Tasks-Active by Project
Filterable
Users+TimeEntries AllTime
Filterable
Pre-blended combo set TIME-ENTRIES
Users+TimeEntries Last X days
Date Rangable
Filterable
Pre-blended combo set TIME-ENTRIES

Built for Synchronization

This service is designed to help anyone continuously export (i.e. "sync") bulk data from Clockify.

If you only need to export your data one time, check the website of Clockify to see if their service offers a one-time export feature natively. Sometimes a Data Source's native export feature may provide not as much data as its API does, in which case Flatly is the solution.

Additional Information

Flatly uses official API channels to provide an integration with Clockify.
Clockify is a simple time tracker and timesheet app that lets you and your team track work hours across projects.
Scopes

Flatly's access to Plaid and Plaid's downstream connected financial institutions is read-only access to text. It is limited to account data (words, numbers, dates). It does not include any money-movement, transfer capabilities or account holder profiles/identities.

Plaid alone interfaces directly with financial institutions, caches data from those institutions on Plaid infrastructure, and then makes the appropriate scoped subset of that data available to partners like Flatly using secure connections called client libraries.

Looker reads tables from Google BigQuery.

File Formats

NDJSON

Integration Flow

Setup

Step 1

Select Clockify from the Data Source dropdown and Google BigQuery from the Data Destination dropdown.

Step 2

Authorize Clockify with your credentials using the Basic Authentication flow.

Step 3

Authorize Google BigQuery with your credentials using the Service Account flow.

Step 4

Select your Data Set from the 8 Data Sets available using the dropdown.

Step 5

Click Flatten to sync your data.

Walkthrough Video

Extended Data Sources

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