No-code pipeline · monday.com → BigQuery

Send data from monday.com to BigQuery

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From monday.com to BigQuery: managed, scheduled, no code.

Kondado replicates monday.com data to BigQuery automatically on a configurable schedule, offering five distinct pipelines including Board Items, Activity Logs, and Users, with 142 total fields available for cross-functional analysis and custom reporting.

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Send monday.com Data to BigQuery

How to send monday.com data to BigQuery? Kondado provides a direct connection that replicates your project management data automatically on a configurable schedule, eliminating the need for manual CSV exports or custom API development. Simply connect your monday.com account as a data source, select BigQuery as your destination, and choose which pipelines to activate from the available options. The platform handles the data extraction and loading without requiring any coding, ensuring your team collaboration metrics and task management data flow continuously into your serverless data warehouse for immediate analysis.

Once configured, your Board Settings, Items, and Conversations data becomes available in BigQuery for advanced analytics and SQL-based exploration. You can combine this operational data with other business sources to create comprehensive dashboards that track project velocity, resource allocation, and team productivity across your entire organization, enabling data-driven decisions that optimize your workflows.

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The Board Items pipeline delivers essential tracking information including item names and update timestamps directly into your BigQuery dataset, enabling you to analyze project progression and identify bottlenecks in your workflows. With the Activity Logs pipeline, you gain access to detailed event histories that record every action taken within your boards, allowing you to audit user interactions and measure team engagement patterns over time. The Users pipeline brings identity and creator information into your warehouse, making it possible to correlate task ownership with completion rates and build accountability metrics that drive performance improvements across departments.

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Replicated to BigQuery

monday.com data available for BigQuery

Tables Kondado writes into your BigQuery, on a schedule you control.

available pipelines

142

extractable fields

BigQuery

Destination

Available integrations

Board Settings

Includes fields such as board_id, group_id, and workspace_id, allowing management of specific settings for each board.

Board Items

Contains information such as id, name, and updated_at, essential for tracking and managing items within each board.

Items: Conversations (Updates)

Presents fields such as id, item_id, and created_at, allowing tracking of updates and interactions related to each item.

Activity Logs

Records events with fields such as id, created_at, and event, providing a detailed history of activities performed.

Users

Includes fields such as user_id and creator_name, allowing identification and management of users interacting with items and updates.

See all available data → Send monday.com to BigQuery →

Try out all the features for free for 14 days

How to send monday.com data to BigQuery

Sync data automatically — no code, no manual exports.

Connect monday.com to Kondado

Authenticate your monday.com account through Kondado's interface to establish the data source connection. Grant the necessary permissions to allow the platform to read your Board Items, Activity Logs, and other selected pipelines.

Configure your BigQuery destination

Enter your Google Cloud project details and dataset specifications to designate BigQuery as your target warehouse. Kondado will create the appropriate schema to house your monday.com data structures.

Select pipelines and set schedule

Choose which of the five available pipelines to activate, such as Board Settings or Users, and define your preferred update frequency. You can configure different synchronization intervals for each pipeline to optimize performance and cost.

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Send data from monday.com to other destinations

monday.com > Looker Studio

monday.com > Power BI

Other visualizations

monday.com > Amazon S3

monday.com > BigQuery

monday.com > Excel

monday.com > Google Sheets

monday.com > MySQL

monday.com > PostgreSQL

monday.com > Redshift

monday.com > SQL Server

Choose a tool to visualize your monday.com data

If the software you need is not listed, drop us a messagem. You can use almost every tool

monday.com > Airtable

monday.com > Alteryx

monday.com > Amazon Quicksight

monday.com > BIMachine

monday.com > Cortex

monday.com > Data Studio

monday.com > Geckoboard

monday.com > Grafana

monday.com > IBM Cognos Analytics

monday.com > Klipfolio

monday.com > Looker Studio

monday.com > Looker

monday.com > Looqbox

monday.com > Metabase

monday.com > Microstrategy

monday.com > Pentaho

monday.com > Power BI

monday.com > Qlik Cloud Analytics

monday.com > Qlik Sense

monday.com > Qlik

monday.com > QlikView

monday.com > Redash

monday.com > Superset

monday.com > Tableau

monday.com > BI TOTVS

monday.com > Zoho Analytics

Frequently Asked Questions (FAQ)

Answers about sending monday.com data to BigQuery automatically

How does Kondado replicate monday.com data to BigQuery? ▼

Kondado uses a direct connection to extract data from your monday.com account and load it into BigQuery on a schedule you configure. You select which pipelines to activate, such as Board Items or Activity Logs, and the platform handles the replication automatically. This process requires no manual exports or technical development work from your team.

What monday.com data can I replicate to BigQuery? ▼

You can replicate data from five distinct pipelines covering Board Settings, Board Items, Items: Conversations, Activity Logs, and Users. These pipelines include 142 fields total, capturing everything from workspace configurations and item details to user interactions and conversation histories. This comprehensive coverage ensures your BigQuery warehouse contains complete operational context for analysis.

How often does monday.com data update in BigQuery? ▼

Kondado updates your monday.com data in BigQuery on a configurable schedule that you set according to your business needs. Choose from intervals as frequent as every five minutes for near-real-time visibility, or select hourly, daily, or custom schedules that balance data freshness with query costs. You maintain full control over the synchronization timing for each pipeline individually.

What format does monday.com data take in BigQuery? ▼

Your monday.com data arrives in BigQuery as structured datasets that mirror the field names and data types from your source, including timestamps, identifiers, and text fields from each pipeline. The schema preserves relationships between boards, items, and users, enabling you to write SQL queries that join these datasets naturally. This structured format supports immediate analysis in Looker Studio, Power BI, or other business intelligence tools.

Can I combine monday.com data with other sources in BigQuery? ▼

Yes, you can combine monday.com data with information from over 80 additional data sources within your BigQuery environment. Blend your project management metrics with CRM data, financial records, or marketing analytics to create unified reports that reveal cross-functional insights. This consolidation enables you to correlate task completion rates with sales performance or budget allocation in single comprehensive dashboards.

Do I need coding skills to send monday.com data to BigQuery? ▼

No coding skills are required to configure the monday.com to BigQuery pipeline through Kondado's no-code interface. The platform provides a guided setup process where you authenticate your monday.com account and map fields visually without writing SQL or API calls. Technical and non-technical users alike can establish automated data flows within minutes.

Can I send monday.com data to destinations other than BigQuery? ▼

Absolutely, Kondado supports sending monday.com data to multiple destinations beyond BigQuery, including PostgreSQL, Google Sheets, MySQL, Redshift, and Amazon S3. You can configure different pipelines to route to different destinations simultaneously, allowing your analysts to access data in their preferred environment while maintaining a central warehouse in BigQuery.

Try out all the features for free for 14 days

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