How does Kondado replicate Zendesk data to Redshift?

Kondado connects to your Zendesk account using your API credentials and extracts data from your selected pipelines. The platform then automatically loads this information into your Redshift cluster on your configured schedule, handling schema creation and updates without requiring manual intervention.

What Zendesk data can I replicate to Redshift?

You can choose from 12 available pipelines including Tickets, Users, Ticket Metrics, Ticket Comments, and Satisfaction Surveys. Each pipeline contains specific fields such as ticket IDs, timestamps, satisfaction scores, and comment text, totaling 235 fields available for analysis in your data warehouse.

How often does Zendesk data update in Redshift?

Kondado offers configurable update schedules ranging from every 5 minutes to daily, allowing you to balance data freshness with processing costs. You can adjust these intervals based on your reporting needs, ensuring your Redshift database reflects the most recent customer service activity.

Can I combine Zendesk data with other sources in Redshift?

Yes, once your Zendesk data is in Redshift, you can join it with information from CRM systems, marketing platforms, or financial databases already in your warehouse. This allows you to create comprehensive reports correlating customer support interactions with sales performance and marketing campaigns.

What format does Zendesk data take in Redshift?

Kondado creates structured tables in Redshift for each selected pipeline, preserving data types from Zendesk such as timestamps, text fields, and numeric values. The schema includes standard fields like IDs and created_at dates, making it easy to query using SQL or connect to Power BI and Looker Studio for visualization.

Do I need technical skills to set up the Zendesk to Redshift pipeline?

No coding is required to establish the connection, as Kondado provides a no-code interface for authenticating Zendesk and configuring your Redshift destination. The platform manages the technical aspects of data extraction and loading, though basic SQL knowledge helps when querying the replicated data.

Can I analyze Zendesk ticket comments in Redshift?

Yes, the Ticket Comments pipeline replicates the full text of customer conversations and agent responses into Redshift. This enables you to perform text analysis, sentiment scoring, and keyword extraction using SQL queries or business intelligence tools connected to your data warehouse.

How do I handle deleted Zendesk tickets in Redshift?

The Closed and Deleted Tickets pipeline specifically captures information about removed tickets, including deletion timestamps and previous status fields. This ensures your Redshift data warehouse maintains a complete historical record for compliance and auditing purposes, even for tickets no longer visible in Zendesk.

Send data from Zendesk to Redshift

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Send Zendesk Data to Redshift Automatically

Kondado provides a direct connection between Zendesk and Redshift, allowing you to replicate your customer service data without writing code. Simply authenticate your Zendesk account, configure your Redshift cluster as the destination, and select which pipelines you want to replicate. The platform handles the data extraction and loading automatically on your chosen schedule, ensuring your data warehouse always contains fresh information for analysis and reporting.

Kondado replicates data from Zendesk to Redshift through 12 available pipelines covering 235 fields, including Tickets, Users, Ticket Metrics, and Satisfaction Surveys, with automated updates running on configurable schedules from every 5 minutes to daily.

Once your data arrives in Redshift, you can combine customer service metrics with information from BigQuery, PostgreSQL, or other business tools to create unified reports. This enables deeper analysis of customer satisfaction trends, agent performance, and support resolution patterns directly within your AWS data warehouse environment, giving your team the insights needed to optimize customer experience strategies.

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

The available pipelines include Ticket Metrics and Satisfaction Surveys, which deliver essential performance indicators directly into your Redshift cluster. By analyzing these datasets alongside your existing business data, you can calculate average response times, track customer satisfaction scores over time, and identify bottlenecks in your support workflow. Additionally, the Ticket Comments pipeline provides the full text of customer interactions, enabling sentiment analysis and quality assurance reporting when combined with user behavior data from Google Sheets or other sources already stored in your data warehouse.

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Zendesk data available for Redshift

available pipelines

235

extractable fields

Available integrations

Integration	Description
Closed and Deleted Tickets	Includes deleted tickets with fields like id, actor_id, and deleted_at, allowing analysis of previous status and ticket description.
Ticket Comments	Contains comments related to tickets, with fields like ticket_id, author_id, and created_at, along with the comment body.
Ticket Metrics Events	Records SLA metric events, including id, metric, and sla_target, allowing performance monitoring of tickets.
Groups	Lists groups with fields like id, name, and updated_at, along with information about the group's status and description.
Ticket History	Records ticket audits with fields like id, ticket_id, and created_at, along with metadata about the source and channel.
Jira Links	Information about links between tickets and Jira tasks, allowing integration and tracking of related tasks.
Tags	Contains information about tags associated with tickets, facilitating categorization and search of tickets by tag.
Ticket Metrics	Presents ticket performance metrics, including response time and resolution time, essential for efficiency analysis.
Organizations	Lists organizations with fields like id, name, and created_at, allowing management and categorization of tickets by organization.
Satisfaction Surveys (Scores)	Collects satisfaction survey results, including id, ticket_id, and score, essential for measuring customer satisfaction.
Tickets	Contains information about tickets, including id, status, and timestamps such as created_at and deleted_at.
Users	Stores data about users, including id, name, and contact information such as email and status.

Closed and Deleted Tickets

Includes deleted tickets with fields like id, actor_id, and deleted_at, allowing analysis of previous status and ticket description.

Ticket Comments

Contains comments related to tickets, with fields like ticket_id, author_id, and created_at, along with the comment body.

Ticket Metrics Events

Records SLA metric events, including id, metric, and sla_target, allowing performance monitoring of tickets.

Groups

Lists groups with fields like id, name, and updated_at, along with information about the group's status and description.

Ticket History

Records ticket audits with fields like id, ticket_id, and created_at, along with metadata about the source and channel.

Jira Links

Information about links between tickets and Jira tasks, allowing integration and tracking of related tasks.

How to send Zendesk data to Redshift

Sync data automatically — no code, no manual exports.

Connect Your Zendesk Account

Authenticate your Zendesk data source in Kondado by providing your API credentials, allowing the platform to access your customer service data for replication.

Configure Redshift Destination

Enter your Redshift cluster connection details including host, database name, and credentials to establish the target location where your Zendesk pipelines will be loaded.

Select Pipelines and Schedule

Choose which of the 12 available Zendesk pipelines to replicate and set your preferred update frequency, from every 5 minutes to daily, to keep your Redshift data current.

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