Zendesk Chat to BigQuery – Made Easy
Replicate Zendesk Chat to BigQuery in minutes
Zendesk Chat is the fastest way to engage your customers with live chat software. Companies want to move this data to a single location or warehouse for easy access and seamless analysis. Replicating Zendesk Chat data to BigQuery ensures the data in your warehouse is always up to date and accessible by analysts and engineers. By moving Zendesk Chat data to BigQuery, you can consolidate this data next to marketing, sales, support, and other data sources and turn your data into valuable and actionable insights.
Why integrate Zendesk Chat with BigQuery?
Businesses today generate huge amounts of data and this data is scattered across different systems and applications. Companies using chat support platforms like Zendesk Chat typically feed this data and data from other sources like advertising, sales, and service to a cloud data warehouse for easier and faster analytics. Integrating your Zendesk Chat to BigQuery will significantly simplify and accelerate the time it takes to build automated reporting. Integrate your chat data and explore it in the context of other business insights to figure out what’s driving leads, prospects, sales, and customer engagement.
Zendesk Chat Overview
Zendesk Chat is an online marketing, live chat support, and web analytics product offered as a SaaS model. The product enables companies to chat with visitors in real-time on their websites. The Zendesk Chat app will let you answer your customer’s questions in real-time and ease them into a purchase.
Google BigQuery Overview
BigQuery is a serverless, highly scalable, and cost-effective cloud data warehouse designed for business agility. This cloud-based enterprise data warehouse offers rapid SQL queries and interactive analysis of massive datasets. It is a powerful tool for business intelligence and it offers analytics capabilities to organizations of all sizes. BigQuery leverages Google’s existing cloud architecture, as well as different data, ingest models that allow for more dynamic data storage and warehousing.
How to replicate Zendesk Chat to BigQuery?
Here are two approaches you can use to replicate Zendesk Chat data to BigQuery. This will allow you to evaluate the pros and cons of both and choose the one that best suits your requirement.
Build your own data pipeline
This process needs a lot of experience and consumes a lot of time and manpower. The chances of errors are more due to the multiple integrated steps one after the other. You need to extract data using Zendesk Chat APIs & then connect it properly with the BigQuery data warehouse. This whole process to build a custom data pipeline requires regular intervention that makes it cumbersome.
Use Daton to integrate Zendesk Chat to BigQuery
Integrating Zendesk Chat to BigQuery with Daton is the fastest & easiest way to save your time and efforts. Leveraging a cloud data pipeline like Daton significantly simplifies and accelerates the time it takes to build automated reporting.
Configuring data replication on Daton only takes a few minutes and a few clicks. Your analysts do not have to write any code or manage any infrastructure, yet you can get access to Zendesk Chat data in a few hours.
Daton’s simple and easy-to-use interface allows analysts and developers to use UI elements to configure data replication from Zendesk Chat to BigQuery.
Daton takes care of:
- Rate limits
- Historical data load
- Incremental data load
- Table creation, deletion, and reloads
- Refreshing access tokens
and many more important functions that are required to enable analysts to focus on analysis rather than worrying about the data that is delivered for analysis.
Steps to integrate Zendesk Chat with Daton
- Sign in to Daton
- Select Zendesk Chat from the integrations page
- Provide Integration Name, Replication Frequency, and History. Integration name would be used in creating tables for the integration and cannot be changed later
- You will be redirected to Zendesk Chat log in for authorizing Daton to extract data periodically
- Post successful authentication, you will be prompted to choose from the list of available Zendesk Chat accounts
- Select required tables from the available list of tables
- Then select all required fields for each table
- Submit the integration
Here are more reasons to explore Daton for Zendesk Chat to BigQuery Integration
- Faster integration – Zendesk Chat to BigQuery is one of the integrations Daton can handle very conveniently and seamlessly. By following a few steps you can easily connect Zendesk Chat to BigQuery.
- Low Effort & Zero Maintenance – Daton automatically takes care of all the data replication processes and infrastructure once you sign up for a Daton account and configure the data sources. No need to manage infrastructure or write manual code.
- Data consistency guarantee and an incredibly friendly customer support team ensure you can leave the data engineering to Daton and focus on analysis and insights!
- Enterprise-grade data pipeline at an unbeatable price to help every business become data-driven. Get started with a single integration today for just $10 and scale up as your data needs grow.
- Robust Scheduling Options: allows you to schedule jobs based on their requirements using a simple configuration step.
- Support for all major cloud data warehouses including Google BigQuery, Snowflake, Amazon Redshift, Oracle Autonomous Data Warehouse, PostgreSQL, and more.
- Flexible loading options allow you to optimize data loading behavior to maximize storage utilization and ease of querying.
- Enterprise-grade encryption gives your peace of mind
- Support for 100+ data sources – In addition to Zendesk Chat, Daton can extract data from a varied range of sources such as Sales and Marketing applications, Databases, Analytics platforms, Payment platforms, and much more.
Daton automates the entire data migration securely and reliably for you. You can now load Zendesk Chat data to any data warehouse such as Redshift, Snowflake, or a destination of your choice without writing code in just a few minutes with Daton.