Big Data Analytics: A Guide to Data Science Practitioners Making the Transition to Big Data

Author:   Ulrich Matter (Assistant Professor of Economics at Uni of St. Gallens, Switzerland.)
Publisher:   Taylor & Francis Ltd
ISBN:  

9781032458144


Pages:   310
Publication Date:   04 September 2023
Format:   Paperback
Availability:   In Print   Availability explained
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Big Data Analytics: A Guide to Data Science Practitioners Making the Transition to Big Data


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Overview

Successfully navigating the data-driven economy presupposes a certain understanding of the technologies and methods to gain insights from Big Data. This book aims to help data science practitioners to successfully manage the transition to Big Data. Building on familiar content from applied econometrics and business analytics, this book introduces the reader to the basic concepts of Big Data Analytics. The focus of the book is on how to productively apply econometric and machine learning techniques with large, complex data sets, as well as on all the steps involved before analysing the data (data storage, data import, data preparation). The book combines conceptual and theoretical material with the practical application of the concepts using R and SQL. The reader will thus acquire the skills to analyse large data sets, both locally and in the cloud. Various code examples and tutorials, focused on empirical economic and business research, illustrate practical techniques to handle and analyse Big Data. Key Features: - Includes many code examples in R and SQL, with R/SQL scripts freely provided online. - Extensive use of real datasets from empirical economic research and business analytics, with data files freely provided online. - Leads students and practitioners to think critically about where the bottlenecks are in practical data analysis tasks with large data sets, and how to address them. The book is a valuable resource for data science practitioners, graduate students and researchers who aim to gain insights from big data in the context of research questions in business, economics, and the social sciences.

Full Product Details

Author:   Ulrich Matter (Assistant Professor of Economics at Uni of St. Gallens, Switzerland.)
Publisher:   Taylor & Francis Ltd
Imprint:   Chapman & Hall/CRC
Weight:   0.453kg
ISBN:  

9781032458144


ISBN 10:   1032458143
Pages:   310
Publication Date:   04 September 2023
Audience:   College/higher education ,  Professional and scholarly ,  Tertiary & Higher Education ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Reviews

“This book is a superb practical guide for data scientists and graduate students in business and economics interested in data analytics. The combination of a clear introduction to the concepts and techniques of big data analytics with examples of how to code these tools makes this book both accessible and practical. I highly recommend this book to anyone seeking to prepare themselves for the ever-evolving world of data analytics in business and economics research.” - Oded Netzer, Vice Dean for Research, Columbia Business School


This book is a superb practical guide for data scientists and graduate students in business and economics interested in data analytics. The combination of a clear introduction to the concepts and techniques of big data analytics with examples of how to code these tools makes this book both accessible and practical. I highly recommend this book to anyone seeking to prepare themselves for the ever-evolving world of data analytics in business and economics research. - Oded Netzer, Vice Dean for Research, Columbia Business School


Author Information

Ulrich Matter is an Assistant Professor of Economics at the University of St.Gallen. His primary research interests lie at the intersection of data science, political economics, and media economics. His teaching activities cover topics in data science, applied econometrics, and data analytics. Before joining the University of St. Gallen, he was a Visiting Researcher at the Berkman Klein Center for Internet & Society at Harvard University and a postdoctoral researcher and lecturer at the Faculty for Business and Economics, University of Basel.

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