Is JQL falling short in Atlassian Cloud? Discover how to use SQL and Rovo AI in Atlassian Insights/Analytics, connecting sources like Databricks or Google Sheets.
If you manage teams and projects in the Atlassian ecosystem, you know the power of JQL (Jira Query Language) very well. It's fast, intuitive and perfect for answering everyday questions about sprints, statuses and assignments.
But there comes a point when your team needs to answer more complex questions:
- What is the real correlation between resolution time and ticket origin?
- How can we cross-reference engineering progress with billing data or external business metrics?
- Why are we limited when we're on Cloud and don't have direct database access like in the old Data Center environments?
This is where Atlassian's analytics evolution comes into play: Insights / Atlassian Analytics, native SQL support, and the AI boost of Atlassian Rovo.
The challenge: how do you do deep analytics in Cloud without direct DB access?
In Data Center or Server deployments, it was common for data engineers to query direct database replicas. In Cloud, the architecture is different for reasons of scalability, security and governance.
To solve this without losing analytical flexibility, Atlassian offers its analytics platform and Atlassian Data Lake. You no longer have to settle for basic board views or JQL filters: you can now run deep relational queries.
Your two paths with SQL: AI-assisted or full control
One of the great advantages of this architecture is that it democratizes data regardless of your technical level:
- Rovo as your SQL copilot: Can't remember the exact syntax or table schema? You can ask Rovo in natural language directly inside the editor. For example: "Show me the average time to close by priority over the last 6 months". Rovo will generate the SQL query, ready to power charts and dynamic dashboards.
- Custom SQL queries (Full Custom): If you're a data analyst, a developer or you just love a challenge, you can open the SQL editor and write your own queries, aggregations, subqueries and joins to build custom metrics without barriers.
Breaking silos: connect external databases
Jira doesn't live in isolation from the rest of your company. The real power of this analytics environment comes from unifying data. You can connect external sources directly, such as:
- Google Sheets (for budgets, OKRs or operational lists)
- Databricks and cloud data warehouses
- Microsoft SQL Server
- Other relational databases and Data Warehouses
This lets you cross-reference the performance of your Jira workflows with business impact in a single, centralized dashboard.
Want to master this skill? Check out the course by Jira Bro & Quabu Solutions
To put these capabilities into practice step by step, Jira Bro has launched a full course focused on getting the most out of SQL and Rovo within the Atlassian universe.
At Quabu Solutions, as an Atlassian Gold Solution Partner and Marketplace Partner, we're delighted to support this initiative, which raises the bar for the technical community and helps teams make decisions based on real data.
👉 Ready to make the jump from JQL to SQL? Take a look at the course and start transforming the visibility of your projects.
#Atlassian #JiraCloud #Rovo #SQL #Analytics #DataLake #QuabuSolutions