Unlock the full potential of your Zendesk data by integrating it seamlessly with Snowflake. With Hevo’s automated pipeline, get data flowing effortlessly—watch our 1-minute demo below to see it in action!

Integrating your data from Zendesk to Snowflake is essential for companies that prioritize benefits such as advanced SLA compliance reporting, support-driven revenue attribution, and uncovering hidden operational bottlenecks. These benefits are impressive, but setting up the pipeline to achieve these may not be easy for users who are new to building pipelines or have no coding knowledge. Therefore, we have provided you with 2 easy step-by-step methods so you can set up a pipeline for your data from Zendesk to Snowflake.

Effortlessly Move Your Zendesk Data to Snowflake

Hevo’s intuitive platform helps you integrate Zendesk with Snowflake in just a few clicks, so you can supercharge your support analytics and make data-backed decisions effortlessly.

  • Real-Time Data Flow: Sync customer support data from Zendesk to Snowflake with minimal latency.
  • No-Code Simplicity: Connect your Zendesk account to Snowflake without writing a single line of code.
  • Unified Reporting: Combine Zendesk data with other business metrics for comprehensive analysis.
  • High Scalability: Use Snowflake’s serverless architecture to manage large volumes of support data with ease.

Try Hevo and join a growing community of 2000+ data professionals who rely on us for seamless and efficient migrations.

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Why Migrate from Zendesk to Snowflake

  • Scalability: As your customer data grows, you need a platform that can handle it without slowing down. Snowflake’s cloud-native architecture scales seamlessly, so you never have to worry about outgrowing it.
  • Better Data Integration: Snowflake allows you to integrate data from multiple sources. This means combining Zendesk support data with other business data to get a complete picture of customer interactions.
  • Faster Reporting: Snowflake’s performance is lightning-fast. Instead of waiting for Zendesk reports, you can run queries on Snowflake and get the answers you need in seconds.
  • Advanced Analytics: Snowflake supports advanced analytics and machine learning, allowing you to dive deeper into customer behavior and trends compared to the standard reports from Zendesk.
  • Cost Efficiency: Snowflake’s pay-as-you-go model ensures you only pay for what you use. No more overpaying for resources you don’t need, making it more cost-effective in the long run.
  • Security & Compliance: You get top-notch data security and compliance features with Snowflake, ensuring your customer data is protected and you stay on the right side of regulations.
  • Ease of Collaboration: Snowflake allows multiple teams to access the same data simultaneously, making collaboration between support, sales, and marketing teams smoother than ever.

Methods to Connect Zendesk to Snowflake

There are multiple methods that can be used to connect Zendesk to Snowflake and load data easily:

Method 1: Using Zendesk RESTful APIs to Connect Zendesk to Snowflake

Step 1: Extracting Data from Zendesk

  • You can use Zendesk’s REST API to extract data. 
  • Example API call to fetch tickets
GET /api/v2/tickets.json

The API returns JSON-formatted data with fields like id, subject

{  "id":      35436,
   "subject": "Help I need somebody!",
    ...
    },
{   "id":      20057623,
    "subject": "Not just anybody!",
     ...
    },
    ...
  ] }

Step 2: Preparing the Data

  • Additional tables may need to be created to accommodate some of the JSON data if it’s not flattened out (nested).
  • Special care must also be taken to ensure that the data coming out of Zendesk properly corresponds to its equivalent types in Snowflake.
  • Snowflake provides support for many widely used data types. Documentation on Snowflake data types can be found here- Preparing Your Data Files.

Step 3: Loading the Data into Snowflake

The files can be loaded from Snowflake’s stages or from any of its external storage locations.

A. Loading the Data from Snowflake Stages:

  • Use the PUT command to ingest the data into a Snowflake stage. 
  • Use COPY INTO to load it into Snowflake. 
  • The following commands are used to load the data from the respective stage types:

Created Internal Stage:

COPY INTO TABLE1 FROM @Stage_Name

Table Stage Type:

COPY INTO TABLE1 file_format=(Type=’JSON’   Strip_outer_array=”TRUE”)

User Stage Type:

COPY INTO TABLE1 FROM @~/staged file_format=(format_name=’json_format’)

B. Loading from External Storage Locations:

  • You can either load directly from a specific storage location or create an external stage for the location and load from it. 
  • Use COPY INTO with cloud-specific configurations
  • FROM @External_Stage_Name. The following is the code to load from the Amazon S3, GCS, and Microsoft Azure locations respectively:

Amazon S3

COPY INTO TABLE1 FROM s3://bucket CREDENTIALS= (AWS_KEY_ID='YOUR AWS ACCESS KEY' AWS_SECRET_KEY='YOUR AWS SECRET ACCESS KEY') ENCRYPTION= (MASTER_KEY = 'YOUR MASTER KEY') FILE_FORMAT = (FORMAT_NAME = JSON_FORMAT)

GCS

COPY INTO TABLE1 FROM 'gcs://bucket’ STORAGE_INTEGRATION=(Integration_name) ENCRYPTION= (MASTER_KEY = 'YOUR MASTER KEY') FILE_FORMAT = (FORMAT_NAME = JSON_FORMAT)

Microsoft Azure

COPY INTO TABLE1 FROM azure://your account.blob.core.windows.net/container STORAGE_INTEGRATION=(Integration_name) ENCRYPTION= (MASTER_KEY = 'YOUR MASTER KEY') FILE_FORMAT = (FORMAT_NAME = JSON_FORMAT)

Limitations of Using Zendesk RESTful APIs to Connect Zendesk to Snowflake

There are quite a few drawbacks associated with loading the data manually. Some of these are:

  • Real-time Limitations: Using this method does not allow for real-time data updates. A lot of extra code and cron jobs will have to be configured to enable this. 
  • Need Engineering Bandwidth: This method is barely feasible when you have a small engineering team, as it requires a lot of resources that may not necessarily be available to many small-sized teams.
  • Maintenance: This method can return inaccurate data in the event that the Zendesk API is down or if there are any connectivity issues.
  • Hard to Perform Data Transformations: Additional code will need to be written to perform basic data transformations. This can make the process even more time-consuming.

Method 2: Using Hevo Data to Connect Zendesk to Snowflake

Step 1. Configure Zendesk as a Source

Configuring Zendesk source: Zendesk to Snowflake

Step 2: Set up Snowflake as your destination in Hevo

Configuring snowflake: Zendesk to Snowflake
  • Click “SAVE & CONTINUE.” to finish setting up your pipeline.
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Conclusion

In this blog, we have provided 2 easy step-by-step guides on integrating your Zendesk data to Snowflake. This integration is crucial for companies facing issues such as fragmented customer data, manual reporting, repeated issues across accounts, and poor SLA visibility. Although both methods we have provided are effective, we recommend using Hevo’s no-code pipeline tool that streamlines the entire process from real-time replication to transformation without needing to write a single line of code

Sign up for a 14-day free trial with Hevo and streamline your data integration. Also, check out Hevo’s pricing page for a better understanding of the plans.

FAQs on Zendesk to Snowflake

How do I migrate to Snowflake?

To migrate to Snowflake, export data from your current database, use Snowflake’s data loading utilities or services like Hevo, for automatic hassle-free data migration.

How do I load data from the cloud to Snowflake?

Data from cloud storage (AWS S3, Google Cloud Storage, or Azure Blob) can be loaded into Snowflake using Snowflake’s COPY INTO command to import data from external stages.

Can we call a REST API from Snowflake?

Yes, Snowflake can call a REST API using external functions or through tools like Python or JavaScript within Snowflake’s Snowpark.

Rashid Y
Technical Content Writer, Hevo Data

Rashid is a technical content writer with a passion for the data industry. Leveraging his problem-solving skills, he delivers informative and engaging content on data science. With a deep understanding of complex data concepts and a talent for clear, compelling communication, Rashid creates content that informs and captivates his audience.