We all do Data Science on a daily basis but sometimes we forget why we’re really doing it. It’s not to spend hours coding but rather it’s to answer often ambiguous questions.
We learn to ask the right questions at an early age. At an intersection, for example, a child might ask his parent: “Does red mean we must stop or just should stop.” The validity of the question will be confirmed by the answer in that case. Years later we ask questions about all aspects of our lives — jobs, finance, relationships etc. We hope to ask the right questions at the right time. [via Forbes]
The formulation of the right questions (aka hypothesis) is key.
When we take on complex scientific problems using data science, asking the right questions at each stop is critical to the process. Failure to do so may make the difference between frustration and profound innovation. Aim carefully and with proper consideration in order to sculpt the right question. You may not get a second chance. [emphasis mine]