Agile Metrics In Action: How To Measure And Improve Team Performance Av Christopher Davies

DESCRIPTION Project tracking systems, test and build tools, source control, continuous integration, and other built-in parts of the software development lifecycle generate a wealth of data that can be used to track and improve the quality and performance of products, processes, and teams. Although the iterative nature of Agile development is perfect for data-driven continuous improvement, the collection, analysis, and application of meaningful metrics often fades in favor of subjective measures that offer less insight into the real challenges of making better software.   Continuous Improvement: Measuring and enhancing the performance of Agile teams is a practical book that shows how to take the data already being generated to make teams, processes, and products better. It points out which metrics to use to objectively measure performance and what data really counts, along with where to find it, how to get it, and how to analyze it. The book also shows how all team members can publish their own metrics through dashboards and radiators, taking charge of communicating performance and individual accountability. Along the way, it offers practical data analysis techniques, including a few emerging Big Data practices.   KEY SELLING POINTS Straightforward to-the-point writing Contains techniques and tools to improve output Uses everyday examples to get readers up and running quickly Empowers and motivates Agile teams to measure and improve   AUDIENCE The reader will ideally be on or be responsible for a team that is practicing Agile development or is about to begin using Agile development.   ABOUT THE TECHNOLOGY All practices in this book are designed to work with any development process or tool stack. For its examples, this book uses the Groovy scripting language to gather data and Grails to create the web based dashboards and radiators. MongoDB, a flexible database with built in data analysis, is used to dissect and serve up the data.