Inside Data Science
Hackers and the Making of a New Profession
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Data scientists appeared suddenly in the early 2010s and quickly became ubiquitous. Institutions, from established corporations to start-ups, universities to government agencies, scrambled to recruit specialists. Somehow, a loose band of computer experts and hackers integrated established technologies and methodologies--and some questionable ideas--into a distinct profession. Where did data science come from, and why did it gain broad recognition? Inside Data Science examines how data scientists defined their professional role and identity, offering an empirically rich and theoretically ground...
Data scientists appeared suddenly in the early 2010s and quickly became ubiquitous. Institutions, from established corporations to start-ups, universities to government agencies, scrambled to recruit specialists. Somehow, a loose band of computer experts and hackers integrated established technologies and methodologies--and some questionable ideas--into a distinct profession. Where did data science come from, and why did it gain broad recognition? Inside Data Science examines how data scientists defined their professional role and identity, offering an empirically rich and theoretically grounded account of the emergence of a new field. Philipp Brandt met data science's early protagonists in New York City's start-up spaces, coffee shops, and lecture halls, where they displayed a puzzling combination of enthusiasm and uncertainty. At these seemingly casual gatherings, data scientists devised the machinery for seeing the world through datasets while also analyzing the social context of their technical work. Retracing their conversations, Brandt demonstrates how the data scientist role emerged from the collective processing of personal struggles navigating the uncharted space between statistical expertise and coding skills. Offering a novel analytical lens and critical perspective on data science, this book shows how the interplay of personal reflection, technical rigor, and collective scrutiny gave the big-data era, for better or for worse, a human face.
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