Atlassian + Databricks: Unlocking Data Insights with Delta Sharing

Atlassian recently partnered with Databricks to power new data sharing capabilities from Atlassian Analytics, using the Delta Sharing protocol. This partnership allows Atlassian to provide Jira enterprise customers with a simple and flexible way to access and analyze their data from the Atlassian Data Lake. By leveraging Databricks’ open and secure data-sharing technology, Atlassian was able to quickly build a new product that expands its offerings and helps customers gain faster insights. In this blog, we will cover why Atlassian partnered with Databricks, use cases enabled and how Atlassian customers can share data using Delta Sharing.

Data sharing from the Atlassian data lake, using Delta Sharing

Atlassian Analytics helps customers visualize data across Atlassian products and other data sources, providing holistic insights into how work is accomplished across teams. However, customers may still wish to utilize Atlassian data externally for more complex analysis or to integrate it with Human Capital Management (HCM) or Customer Relationship Management (CRM) applications.

Utilizing data externally can be a slow process. Let's take an example. For customers needing to generate monthly C-level reports, accessing data through FTP or APIs is necessary. Enterprise customers often deal with large datasets, which can lead to hitting rate limits and encountering difficulties in extracting data all at once. Hence, a need for a direct, fast and secure connection to the Atlassian Data Lake.

Delta Sharing provides a one-stop solution for sharing Atlassian data externally. There is no need to move or copy the data and no restriction on whether it can be exported only to a specific ecosystem. Customers can share this data easily with other Databricks customers. Customers can also export this data to Power BI and Tableau tools or utilize programming languages such as Python to build custom scripts to extract the data securely.

With Delta Sharing’s open protocol, Atlassian makes it easy for all its enterprise customers to access and use their Atlassian Data Lake, no matter what tools they prefer. This broad accessibility is a key differentiator of the partnership.

“Atlassian Analytics launched data shares, leveraging Delta Sharing from Databricks, to unlock access to critical cloud data for our customers at scale. It provides flexibility and accelerates customers’ time-to-insight. Delta Sharing’s ecosystem of connectors, enables customers to easily power their environments with data directly from the Atlassian Data Lake.”

— Ben Jackson, Senior Group Product Manager, Data & Analytics, Atlassian

The collaboration between Atlassian and Databricks Delta Sharing was a natural fit for several reasons:

1. Flexibility for Customers: Delta Sharing is an open protocol, meaning customers can connect their Atlassian data to various tools without being locked into a specific vendor.
2. Quick Product Development: By building on Databricks’ Delta Sharing, Atlassian avoided the need to create a complex data-sharing infrastructure from scratch, enabling a faster time to market for Atlassian Analytics.
3. Scalability: The partnership allows Atlassian to scale its analytics capabilities while providing customers with secure access to their data.

Use Cases Enabled by Atlassian Analytics data share

Atlassian Analytics data share opens up several practical use cases for organizations:

• Business Intelligence Integration
  Customers can connect their Atlassian data directly to popular BI tools like Power BI. This enables teams to create dashboards that track project progress, team performance, or bottlenecks without manual data exports.
• Custom Data Workflows
  Organizations can export Atlassian data into their own environments for deeper analysis, custom reporting or data processes. For example, teams can combine Jira issue logs with internal sales data in CRM to measure the impact of engineering efforts on revenue.
• Cross-Team Collaboration
  Teams across different departments can access shared datasets to align on priorities and metrics. For instance, integrating Jira workflows with Human Capital Management (HCM) data enables better resource planning, tracking team capacity, and aligning workforce insights with project goals.
• Data Sharing with Partners
  Companies can securely share site data with external partners or clients. For example, an IT service provider collaborating on the Jira family products can share all of their site data with their clients in one go.
• Governance and Scalability
  When Atlassian data is shared within Databricks, it will be governed by the Unity Catalog. This integration allows Databricks users to implement robust governance policies, ensuring that access controls are effectively applied to the data.

How Data Shares Work in Atlassian Analytics

The data share feature in Atlassian Analytics makes it seamless and secure for customers to securely access and share their Atlassian data. A data share is a read-only collection of tables with the organization’s data from the Atlassian Data Lake. Organization admins can create data shares and credentials for those data shares in Atlassian Analytics.

Here’s how it works:

1. Create a data share
   Admins can create data shares by selecting specific product data from the Atlassian Data Lake. This process involves:
   • Navigating to the Data shares section in Atlassian Analytics.
   • Selecting the site and product.
   • Naming the share and confirming permissions.
   • Creating credentials associated with the data share.
   
   
2. Connect to External Tools
   Once a data share is created, customers receive credentials (such as endpoints and tokens) that allow them to connect to their Databricks Intelligence Platform, other lake technologies and tools like Power BI and Tableau.
3. Secure and Flexible Access
   Data shares are read-only collections of tables, ensuring that customers can securely access live data without risking accidental changes.

See this demo to see how data shares allow you to access Atlassian data in your environments and in any BI tool.

For more details on how to set up a data share in Atlassian Analytics, check out Atlassian’s guide here.

Conclusion

By partnering with Databricks and leveraging Delta Sharing, Atlassian has expanded its capabilities to ensure enterprise organizations can easily analyze key workflow, developer, and team collaboration data in their platform of choice. This partnership enables insights and seamless integration with third-party tools, all built on an open and scalable foundation.

To get started, explore how Atlassian Analytics can help your organization unlock faster insights and streamline data workflows. You can follow Atlassian’s guide to set up a data share and connect it to your preferred analytics tools, such as Power BI. For deeper insights into Atlassian’s integration with Databricks, check out the Empowering Enterprise grade customers with Delta Sharing - an Atlassian Analytics story featuring Atlassian’s use of Delta Sharing.