Abstract
This chapter is a short history of analytics in the era of modern enterprise computing. We focus on the analytics value chain, the sequence of operations that transform raw data into insight for a business user. The story of business analytics over this period, is one of progressive deconstruction of the value chain from fully integrated but closed systems, to open, modular, and increasingly complex processes.
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Researchers use the term “artificial neural network” to distinguish the logical model from an actual neural network, e.g., an animal brain. Since this book is not about the nervous system, we will just use the term “neural network.”
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By “neutral,” we mean that the credit score is influenced by such things as credit history and payment history and does not expressly take the applicant’s demographics into account. Of course, some demographic groups may, on average, have better or worse credit histories than other demographic groups.
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The Clementine team defined “wide” tables as “more than 100 fields.” Today, data scientists routinely work with thousands or even hundreds of thousands of variables.
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International Data Corporation: The Expanding Data Universe: A Forecast of Worldwide Information Growth through 2010 http://www.tobb.org.tr/BilgiHizmetleri/Documents/Raporlar/Expanding_Digital_Universe_IDC_WhitePaper_022507.pdf
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© 2016 Thomas W. Dinsmore
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Dinsmore, T.W. (2016). A Short History of Analytics. In: Disruptive Analytics. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-1311-7_2
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DOI: https://doi.org/10.1007/978-1-4842-1311-7_2
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Publisher Name: Apress, Berkeley, CA
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