Jira to Google BigQuery – Made Easy

Step by step guide to move PostgreSQL to BigQuery into a data warehouse of your choice! ETL/ ELT your eCommerce data easily with Daton

Jira-to-Google-BigQuery-Made-Easy | Saras Analytics
Jira-to-Google-BigQuery-Made-Easy | Saras Analytics

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Jira is an agile project management and bug tracking solution that allows teams to manage their work and offers different products and deployment options. Often this data is spread between different systems and applications, and before analyzing them, one must get them to a scalable data warehouse first. You need a data warehouse solution like BigQuery. Google BigQuery enables super-fast SQL queries using the processing power of Google’s infrastructure. Replicating your Jira data to Google BigQuery can help you summarize data to improve analysis and in turn, increase productivity and performance.

In this article, we will take you through the overview of Jira and BigQuery, why you should consider integrating Jira and Bigquery, and finally two approaches to replicate your data so you can decide which suits your business the best.

 

Why integrate Jira to Google BigQuery

Jira allows teams to manage their work and offers different products and deployment options that are built purposely for software, business, IT, Ops, and more teams. It is critical that this data reaches its optimal destination for centralized storing and data analysis, like a high-performing cloud data warehouse. Integrate your Jira data to Google BigQuery to unlock insights in near real-time and with predictive analytics. With moving your data to Bigquery, easily integrate Jira with major cloud apps and on-premise data sources and translate data into information to plan for future business strategies.

 

Jira Overview

Jira is a software development tool for agile teams to plan, track, and release world-class software. It is highly configurable and flexible to allow for usage in a wide variety of environments and processes. The platform leverages all kinds of project management skills, including software development, Agile project management, bug tracking, scrum management, content management, marketing, professional service management, and so much more.

 

Google BigQuery Overview

Google BigQuery is a powerful, fast, and flexible data warehouse used for analyzing big data. It enables super-fast SQL queries against petabytes of data using the processing power of Google’s infrastructure. You can upload massive datasets into BigQuery machine learning to help you better understand the data. BigQuery is a trusted source to process your data as it will help you securely and cost-effectively process relevant data and turn it into actionable insights for your business.

 

How to replicate Jira to Google BigQuery

Here are two approaches you can use to replicate Jira data to Google 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 multiple integrated steps to be executed one after the other. You need to extract data using Jira 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 Jira to Google BigQuery

Integrating Jira to BigQuery with Daton is the fastest & easiest way to save your time and efforts. Leveraging an eCommerce 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 Jira 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 Jira to Google BigQuery.

Daton takes care of:

  • Authentication
  • Rate limits
  • Sampling
  • Historical data load
  • Incremental data load
  • Table creation, deletion, and reloads
  • Refreshing access tokens
  • Notifications

and many more important functions for data analysts to focus on analysis rather than worrying about data replication.

 

Steps to integrate Jira with Daton

Daton - The Data Replication Superhero
  • Sign in to Daton
  • Select Jira 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 Jira log in for authorizing Daton to extract data periodically
  • Post successful authentication, you will be prompted to choose from the list of available Jira accounts
  • Select required tables from the available list of tables
  • Then select all required fields for each table
  • Submit the integration

Sign up for a trial of Daton Today!

 

Here are more reasons to explore Daton for Jira Google BigQuery Integration

  • Faster integration – Jira to Google BigQuery is one of the integrations Daton can handle very conveniently and seamlessly. By following a few steps you can easily connect Jira 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: This 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 Jira, Daton can extract data from a varied range of sources such as Sales and Marketing applications, Databases, Analytics platforms, Payment platforms, and much more.

For all sources, check our data connectors page.

Daton, a fully managed modern ETL data pipeline gives you a fuss-free means to quickly and easily replicate your data from Jira to Google BigQuery.

Other Articles by Saras Analytics,

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  2. Why Preserving Data Quality is Important for Data Integration?
  3. Snowflake ETL
  4. How to Use WebEngage
  5. Data Engineering and Customized Data Collection