How does the Freshdesk to BigQuery pipeline work?

Kondado connects to your Freshdesk account via API to extract selected data and load it into your BigQuery dataset. The process runs automatically on your chosen schedule, appending new records and updating existing ones based on timestamps. You configure the connection once, and subsequent data transfers require no manual intervention.

What specific Freshdesk data can I replicate to BigQuery?

You can replicate four distinct pipelines containing 87 fields: Agents with availability status and contact details, Contacts with customer information, Tickets with priority and status data, and Ticket Custom Fields with your unique categorization tags. Each pipeline corresponds to a separate table in your BigQuery dataset that you can query using standard SQL.

How frequently does Freshdesk data update in BigQuery?

Update frequency is fully configurable based on your business needs, ranging from every 5 minutes to daily intervals. You set the schedule during initial configuration and can modify it anytime as your analytics requirements evolve. Near-real-time updates ensure your support dashboards reflect current ticket volumes and agent status.

Can I combine Freshdesk data with other sources in BigQuery?

Yes, BigQuery serves as a central warehouse where Freshdesk data can join with information from CRM, sales, or marketing platforms. Create unified customer views by linking Freshdesk Tickets with Salesforce opportunities or HubSpot contacts using SQL joins. The combined dataset supports comprehensive analysis across your entire customer journey.

What format does Freshdesk data take when it arrives in BigQuery?

Data arrives as structured tables with preserved data types, including timestamps, strings, integers, and booleans from your Freshdesk instance. Each pipeline becomes a separate table with columns matching Freshdesk field names, ready for immediate SQL querying. The schema includes standard fields like ticket ID and subject, plus any custom fields you have configured.

Can I send Freshdesk data to destinations other than BigQuery?

Yes, Kondado supports multiple destinations including PostgreSQL , MySQL, Redshift, SQL Server, Amazon S3, Google Sheets , Power BI , and Looker Studio . You can create separate pipelines to send the same Freshdesk data to different destinations simultaneously. This flexibility allows you to maintain data warehouses while also feeding live reports in spreadsheet or BI tools.

Do I need technical skills to replicate Freshdesk data to BigQuery?

No coding is required to establish the connection or configure data replication. The setup process uses a point-and-click interface to authenticate your Freshdesk account and map data to your BigQuery project. Basic familiarity with BigQuery SQL helps for subsequent analysis, but the data transfer itself requires no programming knowledge.

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Freshdesk to BigQuery Data Replication

Kondado provides a direct integration between Freshdesk and BigQuery that automates your customer service data replication without writing code. Connect your Freshdesk account as a data source, configure BigQuery as your destination, and select which pipelines you want to replicate from the available options. The platform handles the data extraction and loading on a configurable schedule, updating your warehouse every 5 minutes, hourly, or daily based on your specific analytics requirements. Once your data arrives in BigQuery, you can combine Freshdesk metrics with other business data sources to build comprehensive customer experience reports and share insights with stakeholders through Looker Studio, Power BI, or Google Sheets. This automated workflow eliminates manual CSV exports and ensures your analytics always reflect current support operations.

Kondado replicates Freshdesk support data to BigQuery automatically on a user-configured schedule, offering four pipelines including Agents, Contacts, Tickets, and Ticket Custom Fields with 87 total fields available for analysis.

Our prices start from $19 USD/month, and you can try Kondado for free for 14 days with no credit card required

Available Freshdesk Pipelines for BigQuery

The Agents and Tickets pipelines deliver essential helpdesk metrics directly into your BigQuery warehouse. Analyze agent availability patterns alongside ticket volume to optimize staffing levels during peak support hours and improve response time forecasting. The Contacts pipeline enriches your analysis with detailed customer information, enabling you to segment ticket resolution times by customer tier or identify high-value accounts requiring priority handling. Combine these datasets to create comprehensive SQL queries that correlate agent performance with customer satisfaction metrics, building actionable reports for your support leadership team through Looker Studio or Power BI.

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Freshdesk data available for BigQuery

available pipelines

extractable fields

Available integrations

Integration	Description
Agents	Table contains information about agents, including ID, name, email, availability status, and last updated timestamp.
Contacts	Table presents contact data, such as ID, name, phone, email, and creation timestamp.
Tickets	Table includes ticket details, such as ID, subject, status, priority, and creation and updated timestamps.
Tickets: custom fields	Table presents custom fields of tickets, including unique ticket ID and associated tags.

Agents

Table contains information about agents, including ID, name, email, availability status, and last updated timestamp.

Contacts

Table presents contact data, such as ID, name, phone, email, and creation timestamp.

Tickets

Table includes ticket details, such as ID, subject, status, priority, and creation and updated timestamps.

Tickets: custom fields

Table presents custom fields of tickets, including unique ticket ID and associated tags.

See all available data →

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How to send Freshdesk data to BigQuery

Sync data automatically — no code, no manual exports.

Connect Your Freshdesk Account

Authenticate your Freshdesk instance by providing your API credentials in the Kondado interface. Select the specific pipelines you want to replicate from the available Agents, Contacts, Tickets, and Ticket Custom Fields options.

Configure BigQuery Destination

Enter your Google Cloud project details and dataset information to establish BigQuery as your data warehouse. Kondado will create the necessary tables in your specified dataset to receive the Freshdesk data.

Select Pipelines and Schedule

Choose which of the four available pipelines to activate and set your update frequency to run every 5 minutes, hourly, or daily. The automated schedule ensures your BigQuery destination stays current with the latest Freshdesk records without manual exports.

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