Data: A Guide to Humans
Unbound Digital (Verlag)
978-1-78352-864-6 (ISBN)
Data is humanity’s most important new resource. It has the capacity to provide insight into every aspect of our lives, the planet and the universe at large; it changes not only what we know but also how we know it. Exploiting the value of data could improve our existence as much as – if not more than – previous technological revolutions.
Yet data without empathy is useless. There is a tendency in data science to forget about the human needs and feelings of the people who make up the data, the people who work with the data, and those expected to understand the results. Without empathy, this precious resource is at best underused, at worst misused.
Data: A Guide to Humans will help you understand how to properly exploit data, why this is so important, and how companies and governments are currently using data. It makes a compelling case for empathy as the crucial factor in elevating our understanding of data to something which can make a lasting and essential contribution to your business, your life and maybe even the world.
Phil Harvey grew up in Dorset and received a Bachelor of Arts in Artificial Intelligence from the University of Sussex. He has done most jobs in IT from cabling under the floor to building computers to working as a programmer for fifteen years, which included five years as a start-up technical founder and CTO. He is the named inventor on a patent and works at Microsoft as a cloud solutions architect for data and AI. @CodeBeard Dr Noelia Jiménez Martínez was born in Argentina, where she became an astrophysicist. She has worked as a data science consultant in London, as an astrophysics researcher at several universities in Europe, and as the head of data science and astrophysics at the publisher Unbound. She holds a PhD in Numerical Astrophysics Applied to Galaxy Formation and Chemical Evolution from UNLP.
Erscheinungsdatum | 03.01.2020 |
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Sprache | englisch |
Maße | 135 x 204 mm |
Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
Informatik ► Theorie / Studium ► Algorithmen | |
Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
ISBN-10 | 1-78352-864-8 / 1783528648 |
ISBN-13 | 978-1-78352-864-6 / 9781783528646 |
Zustand | Neuware |
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