Data Quality and Consistency

Making all fields mandatory at initial data entry point is not always possible or desirable Not doing so, however, can result in data attribute gaps. It is not easy or productive to chase everyone for updates in Jira. Neelix provides a proactive solution to this problem. Data quality templates are configured for a combination of a project, issue type and issue status. These data quality templates can be checked against any collection of issue tickets. It is possible to auto-add “chaser” comments to tickets with data gap when running such checks.

Replace unproductive and disliked policing by a tool that enables the team to improve quality.

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