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Data Science and Analytics Strategy

Data Science and Analytics Strategy

An Emergent Design Approach

Paperback

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  • Release Date: 05/04/2023
  • Barcode: 9781032196329
  • Genre: Computing & The Internet
  • Sub-Genre: Computer Science
  • Imprint: CRC Press
  • Publisher: Taylor & Francis
Data Science and Analytics Strategy

Data Science and Analytics Strategy

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DESCRIPTION

An Emergent Design Approach

This book describes how to establish data science and analytics capabilities in organisations using emergent design, an evolutionary approach that increases the chances of successful outcomes while minimising upfront investment.


This book describes how to establish data science and analytics capabilities in organisations using Emergent Design, an evolutionary approach that increases the chances of successful outcomes while minimising upfront investment. Based on their experiences and those of a number of data leaders, the authors provide actionable advice on data technologies, processes, and governance structures so that readers can make choices that are appropriate to their organisational contexts and requirements.

The book blends academic research on organisational change and data science processes with real-world stories from experienced data analytics leaders, focusing on the practical aspects of setting up a data capability. In addition to a detailed coverage of capability, culture, and technology choices, a unique feature of the book is its treatment of emerging issues such as data ethics and algorithmic fairness.

Data Science and Analytics Strategy: An Emergent Design Approach has been written for professionals who are looking to build data science and analytics capabilities within their organisations as well as those who wish to expand their knowledge and advance their careers in the data space. Providing deep insights into the intersection between data science and business, this guide will help professionals understand how to help their organisations reap the benefits offered by data. Most importantly, readers will learn how to build a fit-for-purpose data science capability in a manner that avoids the most common pitfalls.



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