Atlassian lately partnered with Databricks to energy new information sharing capabilities from Atlassian Analytics, utilizing the Delta Sharing protocol. This partnership permits Atlassian to offer Jira enterprise prospects with a easy and versatile option to entry and analyze their information from the Atlassian Information Lake. By leveraging Databricks’ open and safe data-sharing expertise, Atlassian was capable of shortly construct a brand new product that expands its choices and helps prospects achieve quicker insights. On this weblog, we’ll cowl why Atlassian partnered with Databricks, use circumstances enabled and the way Atlassian prospects can share information utilizing Delta Sharing.
Information sharing from the Atlassian information lake, utilizing Delta Sharing
Atlassian Analytics helps prospects visualize information throughout Atlassian merchandise and different information sources, offering holistic insights into how work is completed throughout groups. Nevertheless, prospects should want to make the most of Atlassian information externally for extra complicated evaluation or to combine it with Human Capital Administration (HCM) or Buyer Relationship Administration (CRM) purposes.
Using information externally is usually a sluggish course of. Let’s take an instance. For purchasers needing to generate month-to-month C-level stories, accessing information by way of FTP or APIs is critical. Enterprise prospects usually cope with massive datasets, which may result in hitting charge limits and encountering difficulties in extracting information unexpectedly. Therefore, a necessity for a direct, quick and safe connection to the Atlassian Information Lake.
Delta Sharing gives a one-stop answer for sharing Atlassian information externally. There is no such thing as a want to maneuver or copy the information and no restriction on whether or not it may be exported solely to a particular ecosystem. Prospects can share this information simply with different Databricks prospects. Prospects may export this information to Energy BI and Tableau instruments or make the most of programming languages equivalent to Python to construct customized scripts to extract the information securely.
With Delta Sharing’s open protocol, Atlassian makes it simple for all its enterprise prospects to entry and use their Atlassian Information Lake, it doesn’t matter what instruments they like. This broad accessibility is a key differentiator of the partnership.
“Atlassian Analytics launched information shares, leveraging Delta Sharing from Databricks, to unlock entry to essential cloud information for our prospects at scale. It gives flexibility and accelerates prospects’ time-to-insight. Delta Sharing’s ecosystem of connectors, allows prospects to simply energy their environments with information instantly from the Atlassian Information Lake.”
— Ben Jackson, Senior Group Product Supervisor, Information & Analytics, Atlassian
The collaboration between Atlassian and Databricks Delta Sharing was a pure match for a number of causes:
- Flexibility for Prospects: Delta Sharing is an open protocol, that means prospects can join their Atlassian information to varied instruments with out being locked into a particular vendor.
- Fast Product Improvement: By constructing on Databricks’ Delta Sharing, Atlassian prevented the necessity to create a fancy data-sharing infrastructure from scratch, enabling a quicker time to marketplace for Atlassian Analytics.
- Scalability: The partnership permits Atlassian to scale its analytics capabilities whereas offering prospects with safe entry to their information.
Use Circumstances Enabled by Atlassian Analytics information share
Atlassian Analytics information share opens up a number of sensible use circumstances for organizations:
- Enterprise Intelligence Integration
Prospects can join their Atlassian information on to fashionable BI instruments like Energy BI. This permits groups to create dashboards that observe mission progress, workforce efficiency, or bottlenecks with out handbook information exports. - Customized Information Workflows
Organizations can export Atlassian information into their very own environments for deeper evaluation, customized reporting or information processes. For instance, groups can mix Jira problem logs with inner gross sales information in CRM to measure the affect of engineering efforts on income. - Cross-Staff Collaboration
Groups throughout completely different departments can entry shared datasets to align on priorities and metrics. For example, integrating Jira workflows with Human Capital Administration (HCM) information allows higher useful resource planning, monitoring workforce capability, and aligning workforce insights with mission targets. - Information Sharing with Companions
Firms can securely share web site information with exterior companions or purchasers. For instance, an IT service supplier collaborating on the Jira household merchandise can share all of their web site information with their purchasers in a single go. - Governance and Scalability
When Atlassian information is shared inside Databricks, it is going to be ruled by the Unity Catalog. This integration permits Databricks customers to implement strong governance insurance policies, guaranteeing that entry controls are successfully utilized to the information.
How Information Shares Work in Atlassian Analytics
The information share characteristic in Atlassian Analytics makes it seamless and safe for patrons to securely entry and share their Atlassian information. A knowledge share is a read-only assortment of tables with the group’s information from the Atlassian Information Lake. Group admins can create information shares and credentials for these information shares in Atlassian Analytics.
Right here’s the way it works:
- Create an information share
Admins can create information shares by choosing particular product information from the Atlassian Information Lake. This course of includes:- Navigating to the Information shares part in Atlassian Analytics.
- Deciding on the location and product.
- Naming the share and confirming permissions.
- Creating credentials related to the information share.
- Connect with Exterior Instruments
As soon as an information share is created, prospects obtain credentials (equivalent to endpoints and tokens) that enable them to connect with their Databricks Intelligence Platform, different lake applied sciences and instruments like Energy BI and Tableau. - Safe and Versatile Entry
Information shares are read-only collections of tables, guaranteeing that prospects can securely entry reside information with out risking unintended modifications.
See this demo to see how information shares help you entry Atlassian information in your environments and in any BI software.
For extra particulars on easy methods to arrange an information share in Atlassian Analytics, take a look at Atlassian’s information right here.
Conclusion
By partnering with Databricks and leveraging Delta Sharing, Atlassian has expanded its capabilities to make sure enterprise organizations can simply analyze key workflow, developer, and workforce collaboration information of their platform of selection. This partnership allows insights and seamless integration with third-party instruments, all constructed on an open and scalable basis.
To get began, discover how Atlassian Analytics will help your group unlock quicker insights and streamline information workflows. You’ll be able to observe Atlassian’s information to arrange an information share and join it to your most well-liked analytics instruments, equivalent to Energy BI. For deeper insights into Atlassian’s integration with Databricks, take a look at the Empowering Enterprise grade prospects with Delta Sharing – an Atlassian Analytics story that includes Atlassian’s use of Delta Sharing.
