We have developed a time view of statuses metrics based on Jira data as part of our engineering benchmarks application Note: This post is written in continuation with the other blog on the engineering metrics. What is time view of statuses metrics? It is the time view graph that shows how many tickets were present in a given set of statuses for each […]
Time analysis of Jira statuses using Python
Where is your engineering team spending most of its time each sprint?
We have been using Python to analyze data in Jira. We have developed sprint metrics (we call them bucket metrics) based on Jira data as part of our engineering benchmarks application. The graphs we produce helps us during sprint retrospective meetings Note: This post is written in continuation with the other blog posts on engineering team metrics An example bucket metric In this […]
How do you know if you have collaborative agile team?
We have developed team collaboration metrics based on the comment history of Jira tickets. It helps us identify people who are not collaborating well on Jira. It also helps us spot imbalances in teams (e.g.: person X is talking ONLY to person Y, or that person Z is really working well with everyone!). Note: This post is written in continuation with […]
Analyze JIRA data with Python
Most of our clients (Agile software teams) use Atlassian Jira for managing tickets and sprints. Every day, we keep updating the Jira for all tasks that are being worked upon. We realized that Jira has huge project/team data logs but Jira reports were not that helpful in capturing work habits of teams. Hence, Qxf2 has ended up developing an ‘Engineering Benchmarks’ […]