Publish fixed dataset versions for repeatable execution.
Test data management for Jira
Test data management connected to the result it produced
Treat test inputs as versioned execution context. Nexus connects reusable datasets and parameters to test cases and executions so teams can review the data behind a result.
Versioned datasetsRow reservationsExecution-level traceability
How it works
Move beyond values buried in test steps
Reusable data becomes difficult to govern when it is copied into individual cases. Nexus provides a dataset model with versions, classifications, parameters, reservations and usage history.
Reserve rows to reduce collisions in shared environments.
Use parameters to run one case across controlled input combinations.
Pin an execution to the dataset version and row that were used.
Review history when data changes invalidate earlier evidence.
Implementation guide
Design for privacy before scale
Prefer synthetic data. Scanning and masking controls help reviewers identify likely personal or sensitive values, but they do not replace organisational data-handling policy or a human review.
Classify datasets as synthetic, masked or sensitive.
Restrict reveal access and record reveal activity.
Exclude masked and sensitive rows from AI example prompts.
Keep provider and support boundaries visible to administrators.
Questions buyers ask
Frequently asked questions
Can a run record the exact dataset version used?
Yes. Executions can be pinned to the relevant dataset version and row so later review has the original context.
Does selecting masked automatically anonymise data?
No. Classification describes the dataset. Your team remains responsible for replacing or protecting identifiers.
Can sensitive rows be sent to AI as examples?
No. Only synthetic rows can be included, and only after the user opts in.
Test the workflow with a real Jira project
Start with one requirement, one cycle and one release decision.