Integrate Zendesk to Google Bigquery in minute
Are you looking for ways to transfer data from Zendesk to Google Bigquery? Here, we have discussed a quick and easy way to do this data migration using an ETL tool: Daton.
With increasing competition, a data-driven approach is of paramount importance in this age of business. E-Commerce companies specifically need to utilize their data to the fullest to stay ahead of their competition, reduce operational costs, increase efficiency and get insights on the business pulse, and make data-driven business decisions. To optimize their business, it becomes necessary to understand the demand and supply trends, maximize revenue, get more ROIs out of Ad campaigns, and offer an engaging and seamless experience for customers.
Get a complete picture of the business by analyzing all the data generated from the various apps, creating separate data silos. Inventory, customer feedback, payment gateway, customer behaviour data need to be studied to optimize processes further. This process takes a lot of time and effort to execute manually, and the analysis would not be very accurate. Thus companies lose out on potential revenue. Top companies use a data warehouse like Google BigQuery to consolidate all the data. Data consolidation enables easier reporting and faster analysis and decisive actions. Integrating all the different sources into a data warehouse is a complicated process that takes a lot of development time and cost. Daton is a highly automated data pipeline that quickly extracts data from Zendesk to Google BigQuery in real-time, without writing down a single line of code.
Why integrate Zendesk to Google Bigquery?
CRM platforms like Zendesk generate data on leads, accounts, and deals. Top companies usually collect marketing campaigns, CRMs, e-commerce platforms, email marketing tools, social media marketing platforms, cloud telephony services. Behavioural patterns of users like wishlists, search history, cart addition, and cart abandonment data also provide great insights into product demand trends. All of this data can be used to project sales trends and allocate marketing and other budgets accordingly to optimize profits. This data is continuously analyzed and helps a business gain insights, minimizing loss and maximizing revenue. Leading companies try to reduce the effort in data mining of multiple data silos. They replicate data from Zendesk, other apps to load in a data warehouse. A cloud data pipeline like daton can ease the hassle of consolidating data from Zendesk to Google BigQuery.
Zendesk Overview
Zendesk is a cloud-based customer support software designed for better customer relationships. It improves customer satisfaction and support customers on multiple channels such as text SMS, web, mobile app, phone, email and social media. It lowers the overall support costs, increases productivity, and enhances customer satisfaction. The full suite of products in Zendesk to meet customer demands starting from help desk platform, live chat to knowledge-base management. The primary support module comes with the Lite version of the chat, call centre and knowledge base. It helps to build a self-service customer portal using features like knowledge-base and community. Coupled with the AI-powered bot, which direct FAQs and low-touch tickets to the portal, the self-service feature reduces the burden of repetitive work off to enable more focus on high-value tickets and engaged leads. Zendesk integrates with popular solutions like Zoho CRM and HubSpot.
Google Bigquery Overview
Google BigQuery is the first serverless data warehouse service which was available in the market. A database administrator architects the schema and optimize the partitions for performance and cost in a Google BigQuery environment. This cloud service automatically scales to fulfil any demands of a query. Google BigQuery service offers an excellent pricing model based on the amount of data processed by incoming queries, not on the storage or the compute capacity for processing queries. The best part about using Google BigQuery is that you can instantly load data to the service as soon as you start using it. The primary requirements are a mechanism to load data into the data warehouse and the ability to write SQL queries.
How to replicate Zendesk to Google Bigquery?
There are two ways in which you can replicate Zendesk to Google Bigquery data warehouse:
Build a data pipeline
This process needs much experience and consumes a lot of time and manpower. The chances of errors are more. You need to extract data using Zendesk APIs & then connect it properly with Google Bigquery data warehouse.
Use Daton to integrate Zendesk & Google Bigquery
Use Daton to integrate Zendesk & Google Bigquery is the fastest & easiest way to save your time and efforts. Leveraging a cloud data pipeline like Daton significantly accelerates and simplifies the time it takes to build automated reporting.
Configuring data replication on Daton only takes a few minutes and a few clicks. You won’t require any code or manage any infrastructure, yet they can access their Zendesk data in a few hours.
Daton is easy and simple to use. The interface allows analysts and developers to use UI elements to configure data replication from Zendesk data into Google Bigquery.
Daton takes care of:
- Authentication
- Rate limits,
- Sampling,
- Historical data load,
- Incremental data load,
- Table creation, deletion &reloads,
- Refreshing access tokens,
- Notifications
And many more important features to help analysts so that they can focus more on data analysis rather than worry about the data migration.
Steps to Integrate Zendesk with Daton
- Sign in to Daton
- Select Zendesk from the Integrations page
- Provide Integration Name, Replication Frequency, and History. The integration name cannot be changed later as it would be used in creating tables for the integration.
- You will be redirected to the Zendesk login page for authorizing Daton to extract data periodically.
- Post successful authentication, you will be prompted to choose from the list of available Zendesk accounts
- Select the required tables from the available list of tables
- Then select all required fields for each table
- Submit the integration
For more information on Zendesk Data Connector, you can visit the linked article.
Sign up for a trial of Daton Today!
Here are more reasons to explore Daton for Zendesk to Google Bigquery Integration.
- Faster Integration of Zendesk to Google Bigquery– Zendesk to Google Bigquery is one of the integrations Daton can handle very fast and seamlessly. By following a few steps, you can easily connect Zendesk to Google Bigquery.
- Zero Effort & Maintenance: Daton takes care of all the data replication processes and infrastructure automatically once you sign up for a Daton account and configure the data sources. You don’t need to manage any infrastructure or write codes.
- You get an incredibly friendly customer support team who ensure that you leave the data engineering to Daton and focus on analysis and insights.
- Daton is an Enterprise-grade data pipeline that you get at an unbeatable price to help every business become data-driven. Get started today for just $10 with a single integration and scale up as your demands increase.
- Robust Scheduling Options: allows you to schedule jobs based on their requirements using a simple configuration step.
- Daton supports popular cloud data warehouses like Snowflake, Google Bigquery, Amazon Redshift, Oracle Autonomous Data Warehouse, PostgreSQL and more.
- Flexible loading options allows optimizing data loading behaviour to maximize storage utilization and ease of querying.
- Enterprise-grade encryption gives your peace of mind.
- Support for more than 100 data sources: In addition to Zendesk, Daton can extract data from various resources like Databases, Sales and Marketing applications, Analytics and Payment platforms. Daton will ensure that all useful data can be transferred to Google Bigquery for generating relevant insights.
Use Daton to ETL the process of replicating data from Zendesk to Bigquery without worrying about the data heavy-lifting.
