Zendesk to BigQuery Migration: 2 Easy Methods

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Do you have a lot of Customer Service data in Zendesk? Do you want to take a deep dive into Zendesk data and perform advanced analysis on it? If yes, then you’ve come to the right place. Transferring your data from Zendesk to BigQuery or any other Data Warehouse of your choice might be an excellent way to perform a comprehensive analysis of your data. This article will help you understand how to easily set up this migration and perform the necessary analysis on it.

What is Zendesk?

Zendesk allows seamless and efficient interaction between customers and your business. It is like a friendly bridge between your business and your customers. If you’ve ever felt overwhelmed trying to manage customer queries, Zendesk is there to save the day.

Features of Zendesk

1. Ticketing System: Manage all customer queries in one place, turning emails, chats, and social messages into trackable tickets.
2. Multi-Channel Support: Customers can reach out from anywhere, and you see all their messages in one universal inbox.
3. Customizable Workflows: Tailor Zendesk to fit your needs with customizable workflows, macros, and branding options.

Using Zendesk feels like having a trusty sidekick that keeps things organized and helps you respond faster.

What is BigQuery?

BigQuery is your friendly neighborhood data wizard. It makes handling massive amounts of data easy and efficient. Think of it as the smart, speedy friend who can analyze vast amounts of information in no time.

Features of BigQuery

1. Scalable Data Warehouse: BigQuery handles data of any size, scaling effortlessly from gigabytes to petabytes.
2. Serverless Architecture: Fully managed, so you focus on data and queries, not server maintenance.
3. Data Security: Data is encrypted in transit and at rest, ensuring robust security and compliance.

BigQuery helps you crunch numbers at lightning speed and easily handle huge datasets, making data operations effortless.

Use Cases to Transfer Your Zendesk Support Data to BigQuery

Now, the question comes: what good will happen from integrating your Zendesk data with Google BigQuery? Here are some listed use cases:

1. Centralized Data Storage: BigQuery allows data centralization from multiple sources. By integrating Zendesk data into BigQuery, you can combine it with other data sources, such as CRM systems, marketing data, and more, creating a comprehensive view of customer interactions and business performance.
2. Enhanced Data Analysis: BigQuery’s powerful analytics capabilities enable more complex queries and data analysis for Zendesk. You can perform advanced analytics, create custom reports, and gain deeper insights into customer support metrics, such as response times, ticket resolution rates, and customer satisfaction.
3. Scalability: BigQuery is built to handle large datasets efficiently. As your Zendesk data grows, BigQuery can scale to accommodate the increasing volume without compromising performance. This is especially useful for organizations dealing with large support tickets and customer interactions.
4. Real-Time Insights: By integrating Zendesk data with BigQuery, you can set up real-time data pipelines to get up-to-date insights. This is crucial for monitoring customer support performance, identifying trends, and responding to issues.
5. Integration with BI Tools: BigQuery integrates seamlessly with popular business intelligence (BI) tools like Looker, Tableau, and Google Data Studio. This makes it easier to create visualizations and dashboards, enabling data-driven decision-making across the organization.
6. Data Security and Compliance: BigQuery offers robust security features, including data encryption and access control. This ensures that your Zendesk data is stored securely and complies with industry regulations and standards.

Methods to Set up Zendesk to BigQuery Migration

Users can set up Zendesk to BigQuery Migration by implementing one of the following methods:

Method 1: Zendesk to BigQuery Migration Using Automated Data Pipelines

The following steps can be implemented to set up Zendesk to BigQuery Migration using Hevo:

• Configure Source: Connect Hevo Data with Zendesk by providing a unique name for your Pipeline, along with details about Zendesk such as the Token, associated Email Address,  your Zendesk sub-domain, etc.

• Integrate Data: Complete Zendesk to BigQuery Migration by providing information about your Google BigQuery destination such as the authorized Email Address, Project ID, etc.

Method 2: Manual Zendesk to BigQuery Migration

Users can manually set up Zendesk to BigQuery Migration by implementing the following steps:

• Step 1: Extracting Data from Zendesk as CSV
• Step 2: Loading CSV Data into Google BigQuery

Step 1: Extracting Data from Zendesk as CSV

• Log in to your Zendesk account.
• Click on the Gear icon in the sidebar and select Reports under the Manage section.
• Under the Reporting section, input the time period over which you wish to export the data and the type of data you wish to export in the Type field.
• Click on Request File next to CSV.

• A background job will now start preparing your file, and you will receive a download link via email once it’s complete.
• Click the link in the Email you receive to download the CSV file containing the required data.

Step 2: Loading CSV Data into Google BigQuery

Once the data has been exported from Zendesk as CSV, it has to be imported into Google BigQuery. Users can easily perform a batch-load job in Python by running the following code:

from google.cloud import bigquery

# Construct a BigQuery client object.
client = bigquery.Client()

# TODO(developer): Set table_id to the ID of the table to create.
# table_id = "your-project.your_dataset.your_table_name"

job_config = bigquery.LoadJobConfig(
    source_format=bigquery.SourceFormat.CSV, skip_leading_rows=1, autodetect=True,
)

with open(file_path, "rb") as source_file:
    job = client.load_table_from_file(source_file, table_id, job_config=job_config)

job.result()  # Waits for the job to complete.

table = client.get_table(table_id)  # Make an API request.
print(
    "Loaded {} rows and {} columns to {}".format(
        table.num_rows, len(table.schema), table_id
    )
)

All data will now get imported into Google BigQuery and you can perform the necessary analysis of your Zendesk data.

Limitations of Manual Zendesk to BigQuery Migration

The limitations of setting up manual Zendesk to BigQuery Migration are as follows:

• This method involves developing custom scripts, which would require a lot of time in development and maintenance.
• No fast standardizations like times, currency conversions, etc., are performed in this method. Users will have to write Python code manually based on their requirements to perform the required transformations.
• Manual Zendesk to BigQuery Migration is a complex process that might be tough to perform for someone who does not have enough technical knowledge of Zendesk and Google BigQuery.
• The process of exporting the data from Zendesk and importing it into Google BigQuery has to be done manually every time the data has to be updated in Google BigQuery.

Streamline your data operations with our resource on moving data from Zendesk to Snowflake. Access clear steps for optimizing your data management process.

Conclusion

This article provided you with a step-by-step guide on how you can set up Zendesk to BigQuery Migration manually or using Hevo. However, there are certain limitations associated with the manual method.

If those limitations are not a concern to your operations, then using it is the best option but if it is, then you should consider using automated Data Integration platforms like Hevo.

FAQ on Zendesk to BigQuery Migration