Atlassian Analytics and Data Lake for Data-Driven Decisions

Atlassian Analytics is now generally available and included with Cloud Enterprise plans for Jira Software, Jira Service Management, and Confluence.

Getting to know Atlassian Analytics

Atlassian Analytics comes with:

• Atlassian Data Lake, a single source of truth for Atlassian data across software, business, and IT workflows
• 20+ out-of-the-box dashboard templates including flow metrics, content adoption, and developer productivity insights
• Flexible low-code/no-code capabilities with visual mode querying and chart templates
• Connections to Snowflake, Amazon Redshift, Google BigQuery, and other databases, so you can incorporate key external data and map work output to results
• Ease-of-use features including advanced chart controls, querying options, permissioning capabilities, and new sharing functionality

What can teams do with Atlassian Analytics

With Atlassian Analytics your teams can truly understand the flow of work between development, IT, and business processes:

• Development leaders can optimize engineering velocity, improve quality, and identify issues at all levels using detailed dashboards for metrics like lead time, cycle time, and throughput.
• IT operations and support teams can proactively spot and fix bottlenecks with out-of-the-box dashboards for request management, incidents, changes, and service performance.
• Business team leads can map marketing deliverables' impact to sales pipeline and spend efficiency in external databases to optimize spend and efficiency across programs.

Understand performance and health across your engineering organization

Atlassian is launching new dashboards with prescriptive scorecards to provide engineering leaders with improved visibility into flow metrics from team to organizational level. Customizable insights on velocity and performance can be tailored to match each organization's way of working. Atlassian Analytics allows teams to build reports across multiple Jira projects and/or instances, tracking key metrics such as lead time, cycle time, and flow efficiency. These tools aim to provide deeper insights beyond raw data, helping organizations increase efficiency and productivity.

Atlassian Analytics is expanding its capabilities to provide more comprehensive data coverage from external tools in the DevOps toolchain. This will allow for reporting on DORA metrics and generate custom reports on team health and performance. The goal is to help leaders identify issues, improve engineering velocity, deliver more value, and make better business decisions.

Richer insights for both IT operations and support teams

Atlassian Analytics offers a complete picture by combining data from both dev and ops tools, providing richer insights for better decision-making around changes and incidents. Service owners can view all services-related data in one dashboard, including costs, incidents, and related deployments.

Database connections to AWS and Snowflake simplify understanding of service delivery costs. Support teams can track agent workloads, resolution times, and customer satisfaction. I&O leaders can monitor business service performance and quarterly trends on a dashboard.

Map the impact of marketing programs to pipeline and spend

Atlassian Analytics provides a program dashboard for marketing effectiveness by blending project data from Jira Work Management, Jira Software, and Jira Service Management. Connectors to databases like Snowflake enable mapping of programs to pipeline and spend information.

Marketing leads can view completed, in-progress, and at-risk pipeline-generating projects, as well as the pipeline cost of at-risk projects.

Additionally, with Confluence data in the Atlassian Data Lake, Confluence admins can track key metrics to understand the usage of spaces, pages, and more.

A part of our connected data foundation

Atlassian Analytics and Atlassian Data Lake are now generally available to unlock the full value of Atlassian data. Quality data is essential for AI, and Atlassian Intelligence leverages AI through internal models and partnership with OpenAI to bring the technology to their cloud products.