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Thriving in a Data World : A Guide for Leaders and Managers /

Currently, every company, no matter its size, is data-driven in one way or another; using data to improve customer experience, as a new value stream, and to stay competitive. However, many business leaders, professionals, and students-such as executives, business analysts, UI/UX designers, project m...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Krishnan, Sangeeta
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York : Business Expert Press, 2022.
Edición:First Edition.
Temas:
Acceso en línea:Texto completo

MARC

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505 0 |a Cover -- Halftitle -- Title -- Copyright -- Dedication -- Description -- Contents -- Testimonials -- Introduction -- Chapter 1: The Ever-Changing Data Ecosystem -- Chapter 2: Essential Data Analytics 101 and Beyond -- Chapter 3: Finding the Right Mix for Your Analytics Team -- Chapter 4: Crack the Data Product Management Code -- Chapter 5: Make ROI From Data Analytics a Reality -- Chapter 6: Why Do You Need Data Literacy? -- Chapter 7: Data Storytelling -- Chapter 8: A Sneak Peek Into Advanced Analytics -- Chapter 9: Data Glossary: Buzzwords -- Conclusion -- Notes -- References 
505 8 |a About the Author -- Index -- Adpage -- Backcover 
520 3 |a Currently, every company, no matter its size, is data-driven in one way or another; using data to improve customer experience, as a new value stream, and to stay competitive. However, many business leaders, professionals, and students-such as executives, business analysts, UI/UX designers, project managers and marketing teams -are forced to interact with data and those who generate data, without being taught the general competencies needed to feel comfortable having these conversations. This book focuses on the foundations needed to be successful in managing and engaging with data analytics initiatives, bridging the gap between creators and users of data. As a management reference guide, it discusses the different types of data strategy needed for succeeding with data, covering topics such as data team composition, types of data analytics, the importance of data storytelling, and identifying data ROI. 
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