As I begin to describe the value of a successful ASSESS, ALIGN, ASSERT and ACHIEVE big data methodology, I am reminded about a fundamental prerequisite: Use Cases.
From Wikipedia:
"a list of steps, typically defining interactions between a role or actor and a system, to achieve a goal."
I am convinced that Big Data benefits from Use Case Decomposition. It's a predecessor - and now an integral part of - Agile Software Construction. I am continually surprised at how well Use Cases assist in the analysis of uncertain data.
The Decomposition part is also worth mentioning. Moving from top to bottom, decomposition let's you break complex tasks into smaller, more understandable elements. When reviewing results, you get the chance to assemble all the composite pieces of information to ensure fundamental requirements have been met. It is also a really nice way for every member of a development organization to say: 'I understand what you are requesting and here's what I plan to do about it'.
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