Agile methodologies and Big Data

Agile methodologies are no longer a novelty. In fact they have spread to many sectors, other than the traditional of software development.

Agile methodologies emerged in the late 80s and early 90s of the last century in the software world, but it is not long ago when they have become popular, thanks in part to the lean paradigm and methodologies such as Scrum and Kanban.

Among the fundamental techniques to support agile methodologies is Scrum, which consists of procedures to manage small teams of people in carrying out a project. Pragsis been applying agile techniques since its inception as a company in 2004.

Scrum in practice is usually applied with other techniques as Kanban, to manage daily workflow, its estimation on cost and scope. It is in this cost estimation tasks where cards like those shown in the picture, are used to estimate with all project participants, the cost of a task.

Agile methodologies have multiple benefits and generally minimize risks in any project.

Big Data projects by their nature, imply a fair degree of uncertainty and risks: not clear objectives, unknown data sources or poor quality, poor management, etc.

That is why agile approaches are very convenient for such scenarios.

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Agile manifesto: