OPUSWatch connector

Kaivo is a fully managed data platform that syncs your OPUSWatch data into a Google BigQuery warehouse and keeps it up to date automatically. There is no pipeline to build and no infrastructure to run, so you can spend your time analysing your HR data instead of moving it.

What is the OPUSWatch connector

Sync your OPUSWatch workforce data into BigQuery with Kaivo to analyse workers, tasks, and sessions across your sites.

Getting started with the OPUSWatch connector

1. Sign up for Kaivo and create a workspace.
2. Connect your OPUSWatch account.
3. Choose which tables to sync.
4. Wait for the initial sync to finish.
5. Query your data in BigQuery or your favourite AI or BI tool.

Authenticating OPUSWatch

Authenticate with your API Key.

Configuring the OPUSWatch connector

When you set up the connector, you provide:

Tables and columns synced from OPUSWatch

Kaivo syncs 14 tables from OPUSWatch into a dedicated dataset in your BigQuery warehouse. Click any table to see its columns and types.

How the OPUSWatch sync works

After the first load, Kaivo keeps your BigQuery warehouse up to date for you. Where OPUSWatch supports it, each sync pulls only new and changed records so it stays fast; otherwise it refreshes the whole table. Every record keeps its original ID, so you won't get duplicate rows.

Frequently asked questions

How long does the initial sync take for OPUSWatch?

It depends on how much history is in your OPUSWatch account. Most initial syncs finish within minutes, while large accounts can take a few hours. After that, syncs only fetch new and changed records, so they're much faster.

Can I sync only some tables or columns?

Yes. You pick which tables to sync when you set up the connection and can change the selection later. Tables you don't select are never copied to your warehouse.

What happens when OPUSWatch's schema changes?

New fields are never added automatically. You choose which fields to sync, so data you haven't selected (sensitive personal data, for example) never lands in your warehouse. When a new field appears, it becomes available for you to add. What happens to removed or renamed fields depends on a table's sync mode: full-refresh tables always match what's currently in OPUSWatch, so dropped fields disappear, while incremental tables keep their existing columns and history, so an old field stays and newly added fields fill in over time.

How do I handle GDPR or data deletion requests?

Your data lives in your own Kaivo-managed BigQuery warehouse, so the most direct option is to delete or anonymise specific records right in BigQuery. If you delete data in OPUSWatch instead, full-refresh tables drop it on the next sync, while incremental tables keep it, so you would remove the row in BigQuery or ask us to run a full refresh. To remove everything, delete the OPUSWatch connector in Kaivo and all of its synced data is deleted with it.

Common use cases for OPUSWatch data

Task tracking

Use tasks and sessions to track work activity over time.

Worker view

Join workers with worker groups to report on activity across the team.

Site reporting

Use locations to compare activity across sites.

Use OPUSWatch data in your AI and BI tools

Once OPUSWatch data lands in your Kaivo-managed BigQuery warehouse, you can explore it with AI tools or any BI tool that connects to BigQuery. Here's how the most common destinations work with OPUSWatch data.

Claude

Use Kaivo's MCP server to give Claude secure, workspace-scoped access to your data. Setup guide →

Power BI

Microsoft's BI tool with a native BigQuery connector. Supports direct query and scheduled refresh. Setup guide →

Data Studio

Free Google BI tool with native BigQuery support. One-click connection to your Kaivo warehouse; great for SMB teams on Google Workspace. Setup guide →

Tableau

The premium analytics standard, with native BigQuery integration. Setup guide →

Google Sheets

Use Connected Sheets to query BigQuery directly from a spreadsheet, with no SQL. Setup guide →

Excel

Connect via Power Query's BigQuery connector. Setup guide →

Metabase

Open-source BI tool with strong BigQuery support. Setup guide →

See our pricing page for OPUSWatch connector pricing and plan details.

Related connectors

• Greenhouse: Sync Greenhouse to BigQuery.
• Kellokortti: Sync Kellokortti to BigQuery.
• Nepton: Sync Nepton to BigQuery.
• Teamtailor: Sync Teamtailor to BigQuery.
• 7shifts: Sync 7shifts to BigQuery.
• Ashby: Sync Ashby to BigQuery.