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Beyond Technology: An Integrative Process Model for Data Analytics
Abstract
Data analytics is a key to unlock the untapped power of knowledge hidden in the trenches of big data in the age of information and intelligence. However, not all analytics efforts can achieve the desired outcomes and impacts. A successfully executed data analytics project relies on the application of an effective process model that facilitates multidisciplinary collaborations and balance technical efficiency with organizational effectiveness. This article introduces an integrated process model for data science and machine learning including its theoretical foundation and step-by-step descriptions and guidelines. The goal of this article is to provide concise, easy-to-follow guidance for data professionals and domain experts to apply this novel process model in their day-to-day collaborative and iterative analytics effort.
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