Data science and analytics strategy : an emergent design approach

By:

Awati, Ailash

Contributor(s):

Scriven, Alexander

Material type: Text

TextSeries: Chapman & Hall/CRC data science seriesPublication details: Boca Raton RC Press, Taylor & Francis Group 2023Description: 1 online resource : illustrationsISBN:

9781003260158
9781032196329
9781000859379

Subject(s):

DDC classification:

005.758 AWA 2023

Contents:

Foreword. Preface. Acknowledgements. Contributors. 1. Introduction. 2. What Is Data Science? 3. The Principles of Emergent Design. 4. Charting a Course. 5. Capability and Culture. 6. Technical Choices. 7. Doing Data Science: From Planning to Production. 8. Doing the Right Thing. 9. Coda. Index.

Summary: 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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Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Book	Symbiosis International University, Dubai	005.758 AWA 2023 (Browse shelf(Opens below))	1	Available		SIU00110
Book	Symbiosis International University, Dubai	005.758 AWA 2023 (Browse shelf(Opens below))	2	Available		SIU00111

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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