Jira + Python + Data Analysis tools + Agile concepts

= Powerful Actionable Insights

Atlassian London User GroupBy Rudiger Wolf

31 Jan 2016

Objective

You will be able to make better use of the data captured in your Jira instance.

Get at the data.

Process the data.

Present the data in an insightful way

Agenda

Who is the speaker?

Context

Python a great all purpose tool

Actionable Agile

Jira-metrics-extract (Python Package)

The End

Who am I?

Studied Electrical & Electronics Engineering

Started Agile journey in 1998 with DSDM

Independent Consultant

Work with small and large organisations (Private and Public sector)

Couple of startups in Dot Com era

Most recently working at MOJ via Agilesphere

What's the first first question you get from your customer about your release?

Excel to the rescue?

How many of you export issue data to excel and then do further processing?

How many of those who export data automate the further processing?

How many of you use Visual Basic for Applications?

Anyone using office-js yet?

Automate to:

speed-up and

make logic explicit

Consider learning PythonPython is a popular programming language that can help to work with your data.

Why Python?

Ease of Learning

It Runs on Any Platform

Great General-Purpose Language

Constantly Improving

Fantastic community

Extensive standard library

Thousands of 3rd party libraries

Save time, learn from and reuse community libraries

How to get started?

1 - Install Python [+ Git + text editor(Sublime,...) ]

2 - Create “Virtual Environment”

3 - Install Libraries/Packages/Modules

4 - Create your program

Libraries/Packages/Modules

https://pypi.org/project/jira/

This library eases the use of the JIRA REST API from Python and it has been used in production for years. As this is an open-source project that is community maintained.

https://pypi.org/project/pandas/

Designed to make working with structured tabular and time series data both easy and intuitive. Goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language.

https://pypi.org/project/jira-metrics-extract/

Utility helps extract data from JIRA for processing with the ActionableAgile Analytics tool (https://www.actionableagile.com/analytics-tools/) OR produce a version of the charts locally.

The Jupyter Notebook

Is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, machine learning and much more.

http://jupyter.org/

Jupyter + jira-metrics-extract + a number of libraries = Fantastic interactive environment to create analysis “recipes”

https://www.oreilly.com/ideas/the-state-of-jupyter

Http://try.jupyter.org https://notebooks.azure.com

Video Zero to Hero Jira Access

Run video.

How does it take to get started extracting data from Jira?

Zero To Hero With Python and Jira 2min

https://www.youtube.com/watch?v=s4hVmiLR0jo

Actionable Agile

Just get the book, watch the conference Videos…

https://leanpub.com/actionableagilemetrics

Actionable Agile Metrics for Predictability is a comprehensive guide on how to use flow metrics and analytics to get the predictability your customers crave.

By Daniel Vacanti

Other thought leaders in Probabilistic Planning

Troy Magennis – Agile Probabilistic forecasting quant @t_magennis http://focusedobjective.com/

Larry Maccherone @LMaccherone

“I got this concept that every decision is a forecast and the reason I say that is that by picking alternative a for instance, you are going to forecast that alternative a has a better outcome for you than alternatives b, c, d, and e.”

Larry Maccherone -

Director of Analytics at AgileCraft, Prior to that, Larry led the Portfolio Insights product line at Rally Software.

https://www.infoq.com/articles/maccherone-agilecraft-data

Jira-metrics-extractInstall

Configure & Run

Data Extract file

Charts

Cumulative Flow Diagram

Release Burnup with forecast (monte carlo - based on past team performance)

Enhance with Jupyter notebook recipe

Enrich Sprint number, Pivot Table

Fill in missing sprint numbers, Extract dependencies

Visualise the dependencies in clickable dependency map

Demo Video

Configure and extract data 3min

https://youtu.be/HSk_aBQmvi0

Further Demos can show you how to:

* Enrich data extract

* Create Pivot Table

* Visualise Dependencies

The End

Knowledge to create an interactive environment

So that you can extract data and iterate toward analysis “recipes”

Quickly

Repeatability

Questions

Twitter : @rnwolf