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How teams transition to agile development methodologies
searchsoftwarequality.techtarget.com/news/article/0,289142,sid92_gci1347417,00.html

searchsoftwarequality.techtarget.com

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Description:
Considerations for transitioning to agile development methods include when in the development cycle to move, agile training and team size and makeup.

Keywords:
software, quality assurance, QA, testing, development, management, SearchQualitySoftware, TechTarget

Keywords (tags)

agile aws dattaray development devops management members methodologies project scrum software team teams training vignette

Content Summary

How to switch your team to agile Suggestions for scaling agile Scrum and requirements gathering Basab Dattaray with Mountain View, Calif.-based Intuit Inc. said his group also brought in an ext... AMS Services, a provider of insurance agency automation products based in Bothell, Wash., also br... The committee was tasked with developing a plan to adopt Scrum. "We gave them a three-month deadl... They then took "10 natural leaders from a 50-person team" and sent them to a Scrum master course,... Not every organization starts with formal training, though -- take Ajira Technologies Inc. CEO Na... With short development cycles, we can't afford to sit in a classroom." Dattaray's group started with what he called a big sprint of six weeks, then moved to four weeks ... Last year, Dattaray said his teams delivered six different products. "The smallest ones had two d... Kinsman said AMS Services also set up cross-functional teams. "Before, the groups were very siloe... The goal was to deliver fully functional software at the end of every sprint. "It was a pretty bi... They were all loners prior to this." The biggest challenge for the teams, Kinsman said, was getting members to break down stories very... For Vignette, having distributed teams was the biggest challenge, Subramanian said. "I think team... Experts share must-have data science skills beyond coding and math Hiring a data scientist is hard enough given the shortage of candidates, but the subtle mix of sk... Deep learning vs. machine learning: The difference starts with data Deep learning may share some characteristics of traditional machine learning, but experienced use... Deep learning models hampered by black box functionality A lack of transparency into how deep learning models work is keeping some businesses from embraci... Search Financial Applications

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