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Why Data Science Projects Fail

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Why Data Science Projects Fail Synopsis

The field of artificial intelligence, data science, and analytics is crippling itself. Exaggerated promises of unrealistic technologies, simplifications of complex projects, and marketing hype are leading to an erosion of trust in one of our most critical approaches to making decisions: data driven.

This book aims to fix this by countering the AI hype with a dose of realism. Written by two experts in the field, the authors firmly believe in the power of mathematics, computing, and analytics, but if false expectations are set and practitioners and leaders don't fully understand everything that really goes into data science projects, then a stunning 80% (or more) of analytics projects will continue to fail, costing enterprises and society hundreds of billions of dollars, and leading to non-experts abandoning one of the most important data-driven decision-making capabilities altogether.

For the first time, business leaders, practitioners, students, and interested laypeople will learn what really makes a data science project successful. By illustrating with many personal stories, the authors reveal the harsh realities of implementing AI and analytics.

About This Edition

ISBN: 9781032660301
Publication date:
Author: Evan Shellsear, Doug Gray
Publisher: Chapman & Hall/CRC an imprint of CRC Press
Format: Paperback
Pagination: 214 pages
Series: Chapman & Hall/CRC Data Science Series
Genres: Data science and analysis: general
IT and information systems management
Project management
Digital and information technologies: social and ethical aspects
Artificial intelligence

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