Paperback. This book will teach you the fundamental tools that are commonly used in data analytics, particularly in quality management and continuous improvement (kaizen). There are also exercises and quizzes to help you become acquainted with these powerful tools, as well as a resource table for quick reference in the appendix.You will learn: 1) The purpose of each tool, when to use it, and how to use it individually, how to synthesize them for complex problems; 2) errors to avoid when collecting and analyzing data; and 3) an overview of the relationship between these tools and data analytics, particularly business intelligence and big data. You will receive a quick reference guide of all 17 tools. The goal is by the end of this book, you will be a data engineer-in-training of these tools and be able to select the appropriate tools for your data analytics projects. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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Detalles bibliogr�ficos

T�tulo: Data Analytics and Quality Management Fundamental Tools (Paperback)
Editor: Independently Published
Fecha de publicaci�n: 2023
Idioma: Ingl�s
ISBN 13: 9798862833232
Encuadernaci�n: Paperback
Estado: new

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Sinopsis

This book will teach you the fundamental tools that are commonly used in data analytics, particularly in quality management and continuous improvement (kaizen). There are also exercises and quizzes to help you become acquainted with these powerful tools, as well as a resource table for quick reference in the appendix.You will learn: 1) The purpose of each tool, when to use it, and how to use it individually, how to synthesize them for complex problems; 2) errors to avoid when collecting and analyzing data; and 3) an overview of the relationship between these tools and data analytics, particularly business intelligence and big data. You will receive a quick reference guide of all 17 tools. The goal is by the end of this book, you will be a data engineer-in-training of these tools and be able to select the appropriate tools for your data analytics projects.

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