7 Steps to driving an efficient Data Science POC

Move Past Simple Evaluation & Bring Value

Bereich: Whitepaper


A proof of concept (POC) is a popular way for businesses to evaluate the viability of a system, product, or service to ensure it meets specific needs or sets of predefined requirements. POCs should prove the larger value of a system, ensuring it’s aligned with forwarding the company’s longer-term strategic objectives. Of course, a POC will also prove that all the proper infrastructure is in place and ultimately remove any risk associated with moving ahead full speed with data science projects at scale.

What does running a POC mean in practice specifically for data science? When it comes to the evaluation of data science solutions, POCs should prove not just that a solution solves one particular, specific problem, but that a system will provide widespread value to the company: that it’s capable of bringing a data-driven perspective to a range of the business’s strategic objectives.

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