Microsoft Outlook to BigQuery connector
€100/month
Sync your Outlook email metadata into BigQuery with Kaivo to analyse volume, response activity, and unread backlog across mailboxes.
What gets synced
Kaivo syncs 5+ Microsoft Outlook tables, including conversations, mailboxes, messages, messages_details, profile, into your BigQuery warehouse.
See all Microsoft Outlook tablesWhat you can do with Microsoft Outlook data
Volume and senders
Use messages to track email volume by sender and date over time.
Unread backlog
Use is_read across messages and mailboxes to see where unread mail piles up.
Conversation activity
Group messages by conversation_id to measure thread length and back-and-forth.
Priority and attachments
Use importance and has_attachments to find high-priority or heavy mail.
Use your Microsoft Outlook data in your AI and BI tools
Once your Microsoft Outlook data lands in your Kaivo-managed BigQuery warehouse, you can explore it with AI tools like Claude or any BI tool that connects to BigQuery. Here is how the most common tools work with Microsoft Outlook data.
Analyze Microsoft Outlook data with Claude
Once your Microsoft Outlook data is in BigQuery you can ask Claude questions about it and get reports and summaries in plain language.
Microsoft Outlook data in Power BI
Connect your Microsoft Outlook data in BigQuery to Power BI and build live dashboards that refresh automatically.
Microsoft Outlook data in Data Studio
Connect your Microsoft Outlook data in BigQuery to Data Studio and build shareable reports that stay up to date.
Microsoft Outlook data in Tableau
Connect your Microsoft Outlook data in BigQuery to Tableau and explore it with interactive visualizations.
Microsoft Outlook data in Google Sheets
Pull your Microsoft Outlook data from BigQuery into Google Sheets for quick analysis and shared reporting.
Microsoft Outlook data in Excel
Pull your Microsoft Outlook data from BigQuery into Excel for quick analysis and reporting.
Start analyzing your Microsoft Outlook data in three easy steps
Connect your Microsoft Outlook account
Connecting to Microsoft Outlook or any of our other 500+ ready-made data sources is quick and doesn't require deep technical knowledge.
Select the data you want to fetch
The tables and columns you select will be stored securely in a fully managed BigQuery data warehouse.
Analyze with your data tool
Plug in your favorite data tool and start analyzing. All the data you selected will be available in an easy-to-use format.
Why get your data connectors from Kaivo
Access all the data you need
Bring together data from your marketing, finance, HR, CRM, and other systems. Select from our 500+ ready-made data connectors or ask for custom connectors.
Use the data tool of your choice
Analyze data and build reports with your favorite tools. No need to learn a new and complicated tool.
Data warehouse included
All Kaivo plans include a fully managed BigQuery warehouse. Get all the benefits of a data warehouse without any of the hassle.
Data always up to date
Schedule automatic data syncs to run as frequently as you need and your reports will always have the latest numbers.
No need to worry about maintenance
Tools, APIs, and databases change, but we keep your data pipelines working and connectors updated.
Data is cleaned and ready for reporting
Raw data from source systems can be hard to use for analytics or reports. Kaivo automatically cleans all data and makes it easy to use.
Data-driven companies sync their data with Kaivo
Answers to your questions
Yes. Kaivo syncs your Microsoft Outlook data into a managed Google BigQuery warehouse and keeps it up to date automatically.
Kaivo syncs 5+ Microsoft Outlook tables, including conversations, mailboxes, messages, messages_details, profile.
Kaivo keeps your Microsoft Outlook data up to date with automatic syncs that you can schedule as often as you need.
No. Kaivo is fully managed, so you can connect Microsoft Outlook and start analyzing without building or maintaining any data pipelines.
The Microsoft Outlook connector is €100 per month plus the Kaivo platform fee. See the pricing page for platform fee details and trial terms.
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