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 you can easily set up this migration and perform the necessary analysis on it.
Table of Contents
Introduction to Zendesk
Zendesk is a Service-first Software-as-a-Service (SaaS) Customer Relationship Management (CRM) product that offers numerous tools designed to improve the relationship between businesses and customers. Zendesk offers business access to numerous tools such as the following:
- Support Suite: A unified agent workspace with a full-service experience across channels that includes Email, Chat, Voice, Messaging, along with advanced features like business rules.
- Sales Suite: A tool that is designed for a Sales team within any business. It offers Live Chat, Voice, SMS, and automate outreach in one place.
- Support Suite: A simple Support Ticket Management system that gives businesses the ability to track, prioritize, and solve customer support requests.
More information about Zendesk can be found here.
Understanding the Key Features of Zendesk
The key features of Zendesk are as follows:
- Easy Set-Up: Most of Zendesk’s features do not require additional configuration and will work as soon as it’s set up.
- Customer Support and Community: Zendesk allows businesses to get constant feedback from customers through the Zendesk platform. Furthermore, Zendesk provides around-the-clock support for all its customers.
- Comprehensive Ticketing System: Zendesk’s Ticketing system brings together requests from various sources such as Social Media platforms, Email, Chat, etc., in one location. This makes it easy for businesses to manage user requests and respond to them quickly.
- Reporting Functionality: Zendesk provides high-level reporting where you can look at an overview of metrics for your Customer Support activity.
Introduction to Google BigQuery
Google BigQuery is a well-known Cloud-based Enterprise Data Warehouse designed for business agility. It gives users the ability to run complex SQL queries and perform an in-depth analysis of massive datasets. Google BigQuery was built on Google’s Dremel technology to process read-only data.
It leverages a columnar storage paradigm that supports immensely fast data scanning, along with a tree architecture that makes querying and aggregating results significantly efficient. Google BigQuery is Serverless and built to be highly scalable. Google utilizes its existing Cloud architecture to successfully manage a serverless design. It also makes use of different data models that gives users the ability to store more dynamic data.
Google BigQuery is fully managed and performs storage optimization on existing data sets by detecting usage patterns and modifying data structures for better results.
More information on Google BigQuery can be found here.
Understanding the Key Features of Google BigQuery
The key features of Google BigQuery are as follows:
- Managed Service: Google handles the performance tuning and backend configuration for Google BigQuery. This is different from many other Data Warehouses where you are required to perform these tasks yourself.
- Distributed Architecture: You do not have to manually manage Compute Clusters as Google manages resources dynamically based on requirements.
- Easy to Use: You only need to load your data into Google BigQuery and then pay for what you use without having to build your own data center.
- Fast and Detailed Insights: Google BigQuery integrates seamlessly with many front-end analytics tools like Google Data Studio, Tableau, Looker, etc. This makes it very easy for businesses to perform an in-depth analysis of their data.
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Get started for Free with Hevo!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: Manual Zendesk to BigQuery Migration
- Method 2: Zendesk to BigQuery Migration Using Hevo Data
Method 1: 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
- 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.
Method 2: Zendesk to BigQuery Migration Using Hevo Data
Hevo helps you directly transfer data from Zendesk and various other sources to Google BigQuery, Business Intelligence tools, Data Warehouses, or a destination of your choice in a completely hassle-free & automated manner. Hevo is fully managed and completely automates the process of not only loading data from your desired source but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.
Sign up here for a 14-Day Free Trial!Hevo takes care of all your data preprocessing needs required to set up Zendesk to BigQuery Migration and lets you focus on key business activities and draw a much powerful insight on how to generate more leads, retain customers, and take your business to new heights of profitability. It provides a consistent & reliable solution to manage data in real-time and always have analysis-ready data in your desired destination.
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.
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.
Visit our Website to Explore HevoHevo helps you directly transfer data from a source of your choice to a Data Warehouse, Business Intelligence, or desired destination in a fully automated and secure manner without having to write the code. It will make your life easier and make data migration hassle-free. It is User-Friendly, Reliable, and Secure.
Details on Hevo’s pricing can be found here. Sign Up for the 14-day free trial today.
