Название: Data Science and Analytics Strategy: An Emergent Design Approach
Автор: Kailash Awati, Alexander Scriven
Издательство: CRC Press
Серия: Data Science Series
Год: 2023
Страниц: 231
Язык: английский
Формат: pdf (true)
Размер: 13.8 MB
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. Before beginning any discussion of the what, how, and why of Data Science, it is necessary to set the scene for where it sits within traditional data- related functions. Data Science itself is not new; many old and well- established analytical techniques have been rebranded as Data Science or Machine Learning (ML) techniques. Be that as it may, there is a general perception that when problems become sufficiently complicated or difficult (both, indeed, quite subjective terms), it is appropriate to label what is being done as being advanced and thus worthy of being called Data Science. This is why we will avoid defining the term and instead discuss what data scientists do, where Data Science fits into the modern organisational landscape, and the elements that are needed in order to do Data Science. In this book we will use the term data analytics stack to describe both the functional and technical elements that are required for Data Science.