How to Connect Zendesk to Snowflake Using 2 Easy Methods?

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Is your organization generating a lot of customer support data in Zendesk? Are you trying to make sense of this data? If this applies to you, then it might make sense for you to transfer your data from Zendesk to a fully managed Data Warehouse platform like Snowflake so you can perform deep analytics on it.

This blog will present 2 ways of moving data from Zendesk to Snowflake. Thus, enabling you to pick the one that best suits your needs.

What is Zendesk?

Zendesk is a customer service support platform that unifies customer activity across multiple channels to enable you to be able to track support-related activity from one location. Zendesk also has CRM functionality and easy integration with CRM tools like Salesforce. This enhances your ability to monitor the entire customer lifecycle in your organization. Additional information on Zendesk’s API can be found in Hevo’s Zendesk Docs.

Key Highlights of Zendesk:

• Customer Feedback: You are able to receive constant feedback from customers through the Zendesk platform. This provides another avenue for your customer service desk to gauge the success of their efforts.
• Ticketing System: Zendesk’s ticketing system brings together requests from multiple channels, enabling fast response times.
• Reporting: Zendesk has reporting capabilities that provide a quick overview of your service desk activities over a specified period of time.
• Integrations: Zendesk provides integrations for many popular CRM and marketing tools like Mailchimp and Salesforce. This makes it particularly handy for the modern business environment. 

What is Snowflake?

Snowflake is a cloud-based data warehouse. It is fully managed and operates using the Software-as-a-Service model. Thus, its users do not have to get involved in any maintenance activities after setting it up. Snowflake is becoming increasingly popular owing to its ease of use, speed and scalability. Snowflake also has separate storage and compute layers. This enables them to be scaled independently of each other and also priced differently.

Key Highlights of Snowflake:

• Low Maintenance: Snowflake does not require software and hardware installations or much infrastructure management from your internal team. This is because much of this is handled on the backend.
• Speed: Already-running queries are not impacted by scaling in Snowflake. Thus, they do not affect running speeds.
• Cloning Functionality: Snowflake allows the creation of instant copies of objects in real-time. These copies store pointers of the original data in a new table and are not deep copies of the original data. Thus, the cloning functionality saves a lot of space when compared to copying in other data warehouses.
• Separate Storage and Compute Layer: Snowflake’s separate storage and compute layer enables versatile scalability – you can scale either one up or down without affecting the other. Also, you only have to pay for what you use as payment for each layer is also independent of the other. 

Read more on Snowflake Dashboards and Other Key Features of Snowsight here.

Why Migrate from Zendesk to Snowflake

Now the question arises, why would you ever want to migrate from Zendesk to Snowflake, what is the need for it?

• 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 we can combine 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.

Migrating from Zendesk to Snowflake gives you the flexibility and power to make smarter, faster decisions with your customer data!

Prerequisites

• Working knowledge of Zendesk.
• Working knowledge of Snowflake.
• A general idea of command-line.
• A Snowflake account.

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
• Method 2: Using Hevo Data to Connect Zendesk to Snowflake

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

This process would require an investment in your engineering team. The high-level steps are as follows:

• Step 1: Extracting Data from Zendesk
• Step 2: Preparing your Data
• Step 3: Loading the Data into Snowflake

Step 1: Extracting Data from Zendesk

Zendesk provides access to its data through its REST API. Zendesk administrators can access this data by making calls to its API. It is imperative that an administrator access the data (or you become a one) as Zendesk limits its data access for security. For example, to access data on tickets, you may use the code GET /api/v2/tickets.json. The data returned will be of the following format

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

Additional information on Zendesk’s API can be found here:

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

We can load the data into Snowflake via SnowSQL (Snowflake’s Command Line Interface) with the help of the COPY INTO SQL statement. The files can be loaded from Snowflake’s stages or from any of its external storage locations.

Loading the Data from Snowflake Stages:

We can use the PUT command to ingest the data into a Snowflake stage. We then 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’)

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. It is easier to load from an external stage as Snowflake encapsulates the required information like the credentials and location, making it easy for you to reference it. Such a stage can be referenced with a simple statement. Example: COPY INTO TABLE1 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

Steps to use Hevo Data:

Hevo focuses on two simple steps to move your data from Zendesk to Snowflake:

Configure Source: Connect Hevo Data with Zendesk by providing a unique name for your Pipeline, along with details about your authorized Zendesk account. You can also choose the historical sync duration for your Zendesk data.

Integrate Data: Load data from Zendesk to Snowflake by providing your Snowflake database credentials such as the username & password. Provide a name for your database, the host, and the port number for your Snowflake database, and connect in a matter of minutes.

Check Out What Makes Hevo Amazing:

• Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
• Schema Management: Hevo takes away the tedious task of schema management & automatically detects schema of incoming data and maps it to the destination schema.
• Minimal Learning: Hevo, with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
• Hevo Is Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
• Incremental Data Load: Hevo allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.
• Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
• Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.

Conclusion

You have learned about Zendesk, Snowflake, and 2 methods that you can use to connect Zendesk to Snowflake. You can now load Zendesk data to any Data Warehouse such as Redshift, BigQuery, Snowflake, or a destination of your choice without writing code a single line of code with Hevo.

FAQs on Zendesk to Snowflake