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What Agile for Data Science projects
Nowadays, Agile is considered one of the most effective approach to Project Management and it is very popular in Digital Transformation programs.
Agile project management methodologies are born in the second half of the XX century. In that period it was recognized that project management frameworks typically applied to civil or mechanical engineering failed to respond to the business needs of software development projects.
The rise of Agile methodologies was mainly an answer to the need of having a faster validation of the output and avoid the creation of products the user won’t like when no budget for change was available.
Nowadays, Agile is also applied to the management of broader Digital Programs, in general, to any case where the final outcome cannot be defined without continuous adaptations.
One of the most popular Agile methodologies is Scrum, which assumes that the development of complex products is better done when small, diversified, and self-organizing teams are given objectives rather than specific assignments.
According to Scrum methodology, the team is free to determine the best way of meeting those objectives, and the workstream is organized in time-boxed iterative and incremental development cycles called Sprints, whose goal is to deliver working versions of the…
