The relationship between Big Data, data science, digital analytics and the skills and abilities needed to optimise marketing decisions

Angela D’Auria Stanton and Wilbur W. Stanton
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Wilbur W. Stanton: Professor of Marketing, Department of Marketing, Radford University, Radford, VA, USA

Applied Marketing Analytics: The Peer-Reviewed Journal, 2016, vol. 2, issue 3, 265-279

Abstract: In this paper the authors present a comprehensive assessment of the evolution of Big Data and its role in creating the need for data science and digital marketing analytics professionals. The authors begin by providing a brief history and evolution of Big Data and follow that with an empirical analysis of the general skills and abilities desired by employers when making an analytics hire. Using job postings on LinkedIn, the demand for various types of analytics will be presented. Two of these, Data Scientist and Digital Analytics Professionals, will be discussed, drawing comparisons from specific position descriptions and job requirements. This analysis clearly demonstrates the similarities and differences between a data scientist and a digital analytics professional. Among the similarities is the growing acknowledgement that data analytics on large and complex data sets requires a new breed of employee — one who has depth of expertise in a specific area of responsibility while also being fully grounded in a domain of importance to a business. Crunching numbers without understanding the context in which they were gathered or understanding the business context of the patterns in the data is a waste of time and money. Companies also benefit by using teams of diverse individuals working with big data in optimising analytics efforts.

Keywords: Big Data; data science; digital analytics; job requirements; position descriptions; marketing analytics (search for similar items in EconPapers)
JEL-codes: M3 (search for similar items in EconPapers)
Date: 2016
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