Data-Driven Insights and Analytics for Measurable Sustainable Development Goals

· ·
· Morgan Kaufmann
Ebook
400
Pages
Eligible
This book will become available on June 2, 2025. You will not be charged until it is released.

About this ebook

As pursuit of the Sustainable Development Goals (SDGs) becomes central to our global mission, there is a growing imperative to understand, measure, and guide actions using data-driven insights. The SDGs encompass a broad spectrum of global challenges, from eradicating poverty and hunger to preserving the environment and fostering peace. To address these issues effectively, one should be able to measure and analyze progress. Data Driven Insights and Analytics for Measurable Sustainable Development Goals bridges the gap between qualitative and quantitative assessments, recognizing that the SDGs are not solely about numbers but also encompass complex social, environmental, and economic dynamics. By merging data science with qualitative analysis, readers can explore how the 5 Parts of SDGs intersect and influence each other, providing a holistic perspective on sustainable development. The book provides readers with an understanding of how to effectively leverage data science models and algorithms using descriptive analytics, allowing us to assess the current state of SDG performance, and thus offering valuable insights into where we stand on these critical goals. In addition, to make informed decisions and drive the SDGs forward, readers need more than just an understanding of the current situation. The book demonstrates the need for prescriptive analytics, a methodology that guides actions. Prescriptive analytics provides actionable recommendations based on data analysis, helping readers to identify specific interventions and policies that can accelerate progress. Furthermore, predictive analytics is vital in anticipating future trends and challenges. By showing how readers can forecast potential obstacles and opportunities, the book presents tools for taking proactive measures to navigate our path toward the SDGs effectively. By offering a data-driven approach, the book ensures that every action taken is based on sound analysis, making a tangible difference in building a better and safer world for all. - Demonstrates how data can be used to measure human well-being and address issues such as poverty, hunger, health, and education - Explains how data science can provide insights into sustainable practices, reduce waste, and protect natural resources - Provides readers with practical guidance on how to approach and solve complex data analysis problems using descriptive, predictive, and prescriptive modeling and analytics

About the author

Tilottama Goswami has received a BE degree with Honors in Computer Science and Engineering from the National Institute of Technology, Durgapur; and an MS degree in Computer Science (High Distinction) from Rivier University, Nashua, New Hampshire, United States. She was awarded a PhD in Computer Science from the University of Hyderabad. Presently, Dr. Goswami is Professor in the Department of Information Technology, Vasavi College of Engineering, Hyderabad, India. She has, overall, 23 years of experience in academia, research, and the IT industry. Her research interests are computer vision, machine learning, and image processing. She has been granted an Australian patent for her research work. Dr. Goswami has been conferred with the Distinguished Scientist Award by IJIEMR-Elsevier SSRN, Vijayawada, India. She is also a recipient of the Women Researcher Award, awarded by the REST Society for Research International, India. Dr. Goswami is the recipient of University Grants Commission- Basic Scientific Research (UGC-BSR) Fellowship (under the Government of India). She has been awarded the Star Team Award for developing efficient software for GeoMedia (GIS), leading to complete customer satisfaction at Hexagon (Intergraph), Hyderabad. She is Editorial Board Member of two international journals and has contributed editorial articles and chapters in Scopus-indexed books. Dr. Goswami is an IEEE Senior Member in IEEE CIS/GRSS Chapter Hyderabad Section. She is presently serving as Chairperson of ACM Hyderabad Deccan Professional Chapter and has also served as ACM-W Chair. Dr. Goswami is an active researcher and contributes to society by delivering workshops and guest lectures, participating as technical program committee, tutorial chair, and reviewer in international conferences and journals. She has delivered more than 20 invited talks in the area of artificial intelligence, machine learning algorithms, statistical methods, computer vision, and color image processing. Dr. Goswami has been convener for international events such as Distinguished Lecture Series, AI Webinar Series, Workshops, and Conclaves. Dr. Goswami actively maintains her industry engagement through industry exchange program and project consultancy on applications of AI in various problem domains.

Dr. Sonal Mobar Roy is an Assistant Professor at the Center for Wage Employment and Livelihoods at the National Institute of Rural Development and Panchayati Raj, Hyderabad, India. Dr. Roy did her master’s in Social Anthropology from Lucknow University and doctorate in Sociology from the Department of Humanities and Social Sciences, Indian Institute of Technology Kanpur. Her doctoral study focused on stigma related to TB and HIV in Ladakh region of India, and the fieldwork was sponsored by Parkes Foundation, UK. Her research interests include Sociology of Health and Education, Culture and Tribal Studies, Rural Development, and Ethnography. She is a member of international editorial boards and has been involved in teaching, training and research at her institute. She has national and international publications to her name and strives to bridge the gap between theory and practice through her writings and research. She has presented paper at universities of repute such as Oxford University, Imperial College London and University of Berkeley, California.

Dr. Sabrina Senatore (Member, IEEE) is currently a Full Professor of Computer Science at University of Salerno, Italy. Her current research interests include the development and application of intelligent systems based on the combination of techniques from Computational Intelligence, Artificial Intelligence, Text Mining, Information Retrieval, Semantic Web, and Intelligent Agents, areas in which she has published extensively. She is an Associate Editor of several international journals, she is a co-editor of Expert Systems with Applications, Elsevier. She is the co-chair of the IEEE CIS Task Force on Intelligent Agents. She has participated in the organization of several international events, in the roles of Technical Program Chair and Session/symposium Chair. She has published more than 120 papers in international journals and books and on the proceedings of international conferences.

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