CRC FOCUS DATA STORYTELLING AND VISUALIZATION WITH TABLEAU A Hands-on Approach Prachi Manoj Joshi and Parikshit Narendra Mahalle Data Storytelling and Visualization with Tableau With the tremendous growth and availability of the data, this book covers understanding the data, while telling a story with visualization including basic concepts about the data, the relationship and the visualizations. All the technical details that include installation and building the different visualizations are explained in a clear and systematic way. Various aspects pertaining to storytelling and visualization are explained in the book through Tableau. Features • Provides a hands-on approach in Tableau in a simplified manner with steps • Discusses the broad background of data and its fundamentals, from the Internet of Everything to analytics • Emphasizes the use of context in delivering the stories • Presents case studies with the building of a dashboard • Presents application areas and case studies with identification of the impactful visualization This book will be helpful for professionals, graduate students and senior undergraduate students in Manufacturing Engineering, Civil and Mechanical Engineering, Data Analytics and Data Visualization.
Data Storytelling and Visualization with Tableau A Hands-on Approach Prachi Manoj Joshi and Parikshit Narendra Mahalle CRC Press, Boca Raton and London First edition published 2023 by CRC Press 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742 and by CRC Press 4 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN CRC Press is an imprint of Taylor & Francis Group, LLC © 2023 Prachi Manoj Joshi and Parikshit Narendra Mahalle Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint. Except as permitted under U.
Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, access www.com or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978- 750-8400. For works that are not available on CCC please contact mpkbookspermissions@tandf.uk Trademark notice: Product or corporate names may be trademarks or registered trademarks and are used only for identification and explanation without intent to infringe.
Library of Congress Cataloging‑in‑Publication Data A catalog record has been requested for this book ISBN: 978-1-032-30991-0 (hbk) ISBN: 978-1-032-31035-0 (pbk) ISBN: 978-1-003-30774-7 (ebk) DOI: 10.1201/9781003307747 Typeset in Times by MPS Limited, Dehradun Contents Preface vii About the Authors ix 1 Introduction 1 1.1 Internet to Internet of Everything (IoE) 1 1.2 Big Data, Properties and Analytics 2 1.3 Issues and Challenges 7 1.4 Conclusion 9 References 9 2 Data Storytelling 11 2.2 Communicating with Data 14 2.5 Conclusion 30 References 31 3 Data Visualization 33 3.1 Need for Visualization 33 3.3 Visualization Myths and Reality 37 3.4 Ethics in Visualization 39 3.5 Right Graph for Right Data 43 3.6 Visualization for Storytelling 46 3.7 Conclusion 47 References 47 4 Visualization with Tableau 49 4.3 Types of Visualizations 56 4.4 Calculated Fields and Null Values 67 v vi Contents 4.6 Creating Stories – A Case Study 72 4.7 Conclusion 74 References 74 5 Conclusion 75 5.3 Research Openings and Future Outlook 76 Index 79 Preface ‘You can claim your right on the work but not on the result’. – Bhagwad Gita Artificial Intelligence (AI) and Machine Learning (ML) are the buzzwords that are now heard. Their applicability is wide and they possess tremendous potential to unveil meaningful insights with analytics. Understanding the data, the patterns and the relationship is a critical factor prior to the selection, development or usage of any AI/ML approaches.
So, the fundamental requirement is understanding the data and communicating effectively through it. The necessity to answer questions for the audience using the data with a story and through visualization is need of the time. This will assist the data scientists and the analysts to make potential decisions, thus addressing the Business Intelligence domain. Considering the above- mentioned factors, it is rightful to provide interested readers with a book that efficiently presents the data with a story in a wide range of impactful visualizations.
With the current range of available visualization tools, one of the most powerful ones – Tableau – will help the reader to move toward effective visualizations. This will enable novice readers and researchers to know and create visualizations based on the data and their needs. With the tremendous growth and availability of data, the book covers understanding the data, while telling a story with visualization. The book offers basic concepts about the data, the relationship and the visualizations.
Through visualizations, a story is conveyed that showcases meaningful insights in the data. The book intends to provide a strong foundation in visualization to a novice reader. All the technical details that include installation and building the different visualizations are explained in a clear and systematic way. Various aspects pertaining to storytelling and visualization are explained in the book allowing the reader to gain an understanding about the importance and applicability of the topic.
A book to start the journey of a budding Data Viz designer!! This book discusses challenges involved in dealing with the data, and the need to present it in a comprehensive way. This book intends to provide a pathway to the reader from story to visualization, thereby addressing the answers required by the target audience. vii viii Preface The main characteristics of this book are as follows: • Provides a hands-on approach in Tableau in a simplified manner with steps • Numerous examples, technical descriptions and real-world scenarios • A simple and easy language for a wide range of stakeholders from a layman to educated users, villages to metros and national to global levels • Presents application areas and case studies with identification of the impactful visualization • Discusses the broad background of data and its fundamentals, from the Internet of Everything to analytics • Emphasizes the use of context in delivering the stories • Presents case studies with the building of a dashboard • A concise and crisp book that provides content from an introduction to building basic visualizations for the novice reader/viz designer In a nutshell, this book displays all information (basics) that a novice and advanced reader needs to know regarding the data – its story and visualization. The book also discusses the selection and use of visualization techniques.
The book also contributes to creating effective visualizations with applicability. Data storytelling, visualizations and their applications to various branches of science, technology and engineering are now fundamental courses in all undergraduate and postgraduate courses in the field. Many universities and autonomous institutes across the globe have started an undergraduate program titled ‘Artificial Intelligence and Data Science’ as well as honors programs in the same subject which are open for all branches of engineering. Thus, this book is useful for all undergraduate students of these courses for a better understanding of data, its visualization, project development and product design in data science, ML and AI.
This book is also useful for a wider range of researchers and design engineers who are concerned with exploring data science for engineering use cases. Essentially, this book is most useful to all entrepreneurs who are interested in starting their start-ups in the field of applications of data science to the civil, mechanical, chemical engineering and healthcare domains as well as related product development. The book is useful for undergraduates, postgraduates, industry, researchers and research scholars in Information and Communications Technology, and we are sure that this book will be well received by all stakeholders. Prachi Manoj Joshi Parikshit Narendra Mahalle About the Authors Dr.
Prachi Manoj Joshi is an Associate Professor and Associate Head with the Department of Artificial Intelligence and Data Science at BRACT’S, Vishwakarma Institute of Information Technology, Pune, Maharashtra, India. She obtained her B.Tech degrees in Computer Engineering from COEP (College of Engineering, Pune), University of Pune, India. She obtained her PhD in Computer Engineering in Machine Learning from COEP, University of Pune. She has more than 15 years of experience in academics and research.
She has co-authored a book on Artificial Intelligence (PHI) and written book chapters for Research Methodology, published by CRC, and has multiple research publications to her credit. She has successfully supervised a plethora of projects for graduate and postgraduate students encompassing the domains of Artificial Intelligence, Data Mining and Machine Learning. Her research interests include Information Retrieval and Incremental Machine Learning. Parikshit Narendra Mahalle is a senior member of the IEEE and Professor and Head of Department of Artificial Intelligence and Data Science at Vishwakarma Institute of Information Technology, Pune, Maharashtra, India.
He obtained his PhD from Aalborg University, Denmark and continued as a Post Doc Researcher at CMI, Copenhagen, Denmark. He has more than 22 years of experience of teaching and research. He is a member of the Board of Studies in Computer Engineering, Ex-Chairman of Information Technology, Savitribai Phule Pune University and various universities and autonomous colleges across India. He has nine patents, more than 200 research publications (Google Scholar citations- 2092+, H index-21 and Scopus Citations are 1000+ with H index-15) and has authored/edited more than 40 books with Springer, CRC Press, Cambridge University Press, etc.
He is the editor in chief for the International Journal of Rough Sets and Data Analysis, Associate Editor for the International Journal of Synthetic Emotions and the Inderscience International Journal of Grid and Utility Computing and a member of the ix x About the Authors Editorial Review Board for the International Journal of Ambient Computing and Intelligence. All these journals are published by IGI Global. His research interests include Machine Learning, Data Science, Algorithms, Internet of Things, Identity Management and Security. He is a recognized PhD guide of SSPU, Pune, and guiding seven PhD students in the area of IoT and Machine Learning.
Recently, four students have successfully defended their PhDs. He has been the recipient of the ‘Best Faculty Award’ by Sinhgad Institutes and Cognizant Technologies Solutions. He has delivered 200+ lectures at national and international levels.1 INTERNET TO INTERNET OF EVERYTHING (IOE) As stated by Mark Weiser [1], the number of devices and users connected to Internet will grow exponentially and cross 30 billion and there will be almost four devices per person on average. There has been also rapid advancement in the broadband technology over the decades resulting into high-speed and low- cost Internet with the wide availability across the globe.
Today, the Internet is driving the world economy as most businesses rely on it and has also became the strongest pillar of e-commerce and m-commerce. In addition, a very large- scale integration technology is advancing at a faster rate producing the powerful processors that are equally dense. This has also contributed to im- prove the density to performance ratio significantly. Another key enabler is the immense transformation in semiconductor industry which has caused drastic decrease in the memory space as well as allied storage services such as cloud.
It has also resulted in lowering of the cost for data storage and man- agement. Due to advancement in high-performance computing, distribution of compute as well as processing power across multiple clusters in a decen- tralized manner has improved significantly. This has also enabled the faster data compute and analysis. Equally the sensor market is also improving in terms of cost and functionalities.