In our Tricentis Analytics November release, we have put more historical data in your hands with new Trend Analysis reports. Also, we have added new Master Visualizations and pulled data from more of your favorite agile planning tools.
Check out the highlights below and start your upgrade today.
Build Trend Analysis Reports from change history data
Stories matter for your reporting. Building reports that don’t tell the right story leaves your data lifeless and unable to effectively communicate. In order to tell good stories, your reports need the proper context. Luckily, this is where Trend Analysis reporting steps in.
Trend Analysis reports rely on your change history data. This data allows you to track how your testing artifacts are changing over time, offering the perfect context.

While there are many uses for this data, two examples might be:
- Identify which flaky automated tests keep running
- See which Jira defect issues are constantly reopened
Our new Trend Analysis helps you to deliver the best reporting stories. Check out the video below to see it in action within Tricentis Analytics.
More drag and drop Master Visualizations
With our July release, we released a brand new set of Master Visualizations to Tricentis Analytics. After gathering your feedback, we’ve added sixteen new pre-made reports to the Master Visualizations panel.
These new reports include:
- Test Run Status by Project
- Defect Status Trend
- Test Case Type Weekly Trend
Check out the video below to see some of the new Master Visualizations that we released today.
Broader visibility for VersionOne and Rally artifacts
Tricentis Analytics has already brought you simple and robust reporting for Jira data. In this release, we’ve broadened the offering. Now, you can easily pull and report against your VersionOne and Rally data.

We have added two new Base Sheets to the six already released last July:
- Explore Rally Defects
- Explore VersionOne Defects
These new Base Sheets will help your team effectively report against your VersionOne and Rally data.
