No-code pipeline · Freshdesk → Amazon S3

Send data from Freshdesk to Amazon S3

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From Freshdesk to Amazon S3: managed, scheduled, no code.

Kondado replicates Freshdesk Agents, Contacts, Tickets, and Tickets Custom Fields to Amazon S3 on a configurable schedule, storing data in a format optimized for query engines like Amazon Athena, Presto, and Dremio.

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Send Freshdesk Data to Amazon S3 Automatically

Kondado provides a direct integration between Freshdesk and Amazon S3, allowing you to replicate your helpdesk data without writing code. Simply connect your Freshdesk account as a data source, configure your Amazon S3 bucket as the destination, and select which pipelines you want to replicate. The platform handles the data extraction and loading automatically on your preferred schedule, whether you need updates every five minutes, hourly, or daily. This automated approach ensures your S3 data lake always contains current customer service information for analysis.

Once your Freshdesk data lands in Amazon S3, you can query it directly with SQL using Amazon Athena or connect it to business intelligence tools like Power BI and Looker Studio for comprehensive customer service analytics and reporting.

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The Agents and Tickets pipelines deliver essential helpdesk metrics directly to your Amazon S3 storage, enabling you to analyze agent performance alongside ticket resolution times using SQL query engines. By replicating the Contacts pipeline alongside ticket data, you can build comprehensive customer profiles that track support history and identify high-value accounts requiring proactive attention. The Tickets Custom Fields pipeline captures your unique Freshdesk configurations, allowing you to segment analysis by product lines, priority tiers, or any custom categorization your team uses to organize support workflows.

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Replicated to Amazon S3

Freshdesk data available for Amazon S3

Tables Kondado writes into your Amazon S3, on a schedule you control.

available pipelines

extractable fields

Amazon S3

Destination

Available integrations

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 → Send Freshdesk to Amazon S3 →

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How to send Freshdesk data to Amazon S3

Sync data automatically — no code, no manual exports.

Connect Freshdesk as Data Source

Enter your Freshdesk API credentials in Kondado to authenticate and establish access to your helpdesk data. This creates the initial connection to your Freshdesk account, allowing the platform to read Agents, Contacts, and Tickets information.

Configure Amazon S3 Destination

Provide your S3 bucket name, region, and IAM credentials to establish where your Freshdesk data will be stored. This setup enables the replication of data into your existing AWS infrastructure for use with Athena or other query engines.

Select Pipelines and Schedule

Choose which of the four available pipelines you want to replicate, such as Tickets and Agents, then set your preferred update frequency from five minutes to daily intervals. This configuration determines which 87 fields arrive in your S3 bucket and how frequently they refresh.

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Send data from Freshdesk to other destinations

Freshdesk > Looker Studio

Freshdesk > Power BI

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Freshdesk > Amazon S3

Freshdesk > BigQuery

Freshdesk > Excel

Freshdesk > Google Sheets

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Choose a tool to visualize your Freshdesk data

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

Freshdesk > Airtable

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Freshdesk > Looker Studio

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Freshdesk > Metabase

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Freshdesk > Pentaho

Freshdesk > Power BI

Freshdesk > Qlik Cloud Analytics

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Freshdesk > Qlik

Freshdesk > QlikView

Freshdesk > Redash

Freshdesk > Superset

Freshdesk > Tableau

Freshdesk > BI TOTVS

Freshdesk > Zoho Analytics

Frequently Asked Questions (FAQ)

Answers about sending Freshdesk data to Amazon S3 automatically

How do I connect Freshdesk to Amazon S3 without coding? ▼

Kondado offers a no-code direct integration that authenticates with your Freshdesk account using standard API credentials. After connecting Freshdesk as your data source, you simply enter your Amazon S3 bucket details and IAM credentials to establish the destination. The platform then automatically extracts your selected pipelines and loads them into S3 according to your configured schedule.

What Freshdesk data can I replicate to Amazon S3? ▼

You can replicate four distinct pipelines containing 87 total fields, including Agents with availability status and email information, Contacts with phone and creation timestamps, and Tickets with subjects, priorities, and status updates. The Tickets Custom Fields pipeline also captures your unique ticket tags and custom field values for specialized reporting needs.

How often does Freshdesk data update in my S3 bucket? ▼

Kondado updates your Amazon S3 data on a configurable schedule that you control, with options ranging from every five minutes to daily intervals. This flexibility allows you to balance data freshness with API rate limits and storage costs based on your specific analytics requirements.

What file format does Freshdesk data use when stored in Amazon S3? ▼

Data arrives in Amazon S3 formatted for immediate use with query engines like Amazon Athena, Presto, and Dremio, supporting efficient SQL analysis without additional transformation. This structure enables you to query large ticket volumes directly from S3 or connect the data to BigQuery and other analytics platforms.

Can I combine Freshdesk data with other sources in Amazon S3? ▼

Yes, you can consolidate Freshdesk helpdesk data alongside information from CRM systems, billing platforms, or product databases within the same S3 data lake. This unified approach enables comprehensive customer journey analysis by joining support tickets with sales data from PostgreSQL or marketing metrics from other sources.

Do I need to manually export CSV files from Freshdesk to get data into S3? ▼

No manual exports are required, as Kondado automatically extracts data through the Freshdesk API and loads it directly into your specified S3 bucket paths. This eliminates the need for manual CSV handling and ensures your data remains current without administrative overhead.

Can I send Freshdesk data from S3 to business intelligence tools? ▼

Absolutely, once your data resides in Amazon S3, you can connect it directly to Power BI, Looker Studio, or BigQuery for visualization and dashboard creation. This workflow allows you to build custom reports that combine helpdesk metrics with financial or operational data from other systems.

What happens when new custom fields are added to Freshdesk tickets? ▼

The Tickets Custom Fields pipeline captures existing custom field structures during the initial setup, and you can modify your pipeline selection within Kondado to include new fields as your Freshdesk configuration evolves. This ensures your S3 data structure adapts to changes in your support workflow without requiring technical reconfiguration.

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