How Is Knowing the Business Important to Data Science?

How Is Knowing the Business Important to Data Science?

How Is Knowing the Business Important to Data Science?
Businesses around the world are involved in a multitude of projects at any given time. As Data Scientists come into the business fold, it becomes more important with each passing day to have both parties – “the business” and “the Data Scientist” – begin to define successful strategies of working together. Businesses are having to become aware of the techniques and methods of a Data Scientist in order to maximize their analytic investments; and, simultaneously, Data Scientists are having to learn how to be relevant to an organization that is in a constant state of change. From a business perspective, knowing what to expect of a Data Scientist and having that Data Scientist develop a reasonable Data Science workflow can create huge competitive advantage over other companies who are lost at the “Data Science Sea.”

Performing a bit of journalistic investigation into the organization’s business situation will help provide a Data Scientist with the necessary context for their Data Science project right off the top. Getting background facts on the business will help the Data Scientist know what he or she is getting involved in – in the truest sense. This may not be obvious to the Data Scientist at first, but learning background facts about the business helps to uncover details that will round out one’s understanding of what the business has determined it needs as it relates to the Data Science project. Through this process, information on identifying resources most certainly bubbles to the surface. The takeaway: even if a Data Scientist has worked at the organization for years, this critical step should not be skipped. The business background is a dynamic concept that speaks to the circumstances or situation prevailing at a particular time – it should not be looked at as part of a one-and-done process. Data Scientists should be careful not to fall into the trap of believing that nothing has changed since the last Data Science project.

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Many Data Scientists forget the essential step of learning about the business from the business’s perspective. Since the business is the customer of the Data Scientist, this can be easily boiled down to “What does the customer truly want to accomplish?” This simple but straightforward question may seem frivolous to an inexperienced Data Scientist, but getting at what the business objectives are for any Data Science project will create a necessary roadmap for moving forward.

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