Social Data Analytics in the Cloud with AI
1st Edition
Will be published approx. on 22. June 2026
Book
Paperback/Softback
166 pages
978-1-032-56906-2 (ISBN)
Description
The rise of cloud computing and Generative artificial intelligence (AI) has revolutionized data analytics pipelines. Analysts can collect, store, and process vast datasets in the cloud with high availability and scalability, and also leverage Generative AI to query and visualize datasets in natural languages. This pioneering textbook provides a gateway for students, educators, and professionals to develop and enhance social data analytics capabilities with the latest cloud computing and AI technologies. The textbook introduces educational cloud resources from leading technology companies, begins with foundational concepts, and progresses to advanced techniques.
Features
The first textbook on cloud-based social data analytics with the assistance of Generative AI.
Introduces educational cloud resources from leading technology companies like AWS, GitHub, and MongoDB.
Presents a fully AI-powered data analytics pipeline from Python coding to data collection with APIs, cloud-based data storage, natural language queries, and interactive visualization.
Analyzes Census and social media data with the latest large language models (LLMs).
Provides hands-on exercises with real-world datasets on timely issues.
This textbook is an excellent resource for upper-level undergraduate and graduate students taking GIS, Urban Informatics, Social Science Data Analysis, and Data Science courses; faculty members teaching such courses; and professionals and researchers interested in leveraging cloud computing and Generative AI in social data analytics.
Features
The first textbook on cloud-based social data analytics with the assistance of Generative AI.
Introduces educational cloud resources from leading technology companies like AWS, GitHub, and MongoDB.
Presents a fully AI-powered data analytics pipeline from Python coding to data collection with APIs, cloud-based data storage, natural language queries, and interactive visualization.
Analyzes Census and social media data with the latest large language models (LLMs).
Provides hands-on exercises with real-world datasets on timely issues.
This textbook is an excellent resource for upper-level undergraduate and graduate students taking GIS, Urban Informatics, Social Science Data Analysis, and Data Science courses; faculty members teaching such courses; and professionals and researchers interested in leveraging cloud computing and Generative AI in social data analytics.
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Academic, Professional, and Undergraduate Advanced
Product notice
Paperback (trade)
Unsewn / adhesive bound
Illustrations
14 farbige Abbildungen, 50 s/w Photographien bzw. Rasterbilder, 13 Farbfotos bzw. farbige Rasterbilder, 24 s/w Zeichnungen, 1 farbige Zeichnung, 27 s/w Tabellen, 74 s/w Abbildungen
27 Tables, black and white; 1 Line drawings, color; 24 Line drawings, black and white; 13 Halftones, color; 50 Halftones, black and white; 14 Illustrations, color; 74 Illustrations, black and white
Dimensions
Height: 234 mm
Width: 156 mm
Thickness: 10 mm
Weight
268 gr
ISBN-13
978-1-032-56906-2 (9781032569062)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Xuebin Wei | Xinyue Ye
Social Data Analytics in the Cloud with AI
Book
12/2024
1st Edition
CRC Press
€123.40
Shipment within 10-20 days
Xuebin Wei | Xinyue Ye
Social Data Analytics in the Cloud with AI
E-Book
12/2024
1st Edition
CRC Press
€104.99
Available for download
Xuebin Wei | Xinyue Ye
Social Data Analytics in the Cloud with AI
E-Book
12/2024
1st Edition
CRC Press
€104.99
Available for download
Persons
Dr Xuebin Wei is an associate professor at James Madison University (JMU) and an AWS Academy Certified Educator. He earned a Ph.D. in Geography from the University of Georgia in 2015. Dr Wei has developed a series of cloud-based technology courses that promote an engaged and inclusive learning environment and helps current students prepare for future careers. He was selected as a Faculty Ambassador of the AWS Educate Cloud Ambassador Program and received the JMU Excellence in Teaching & Learning with Technology Award in 2019.
Dr Xinyue Ye is the Harold L. Adams Endowed Professor in the Department of Landscape Architecture & Urban Planning, Department of Geography, and Department of Computer Science & Engineering at Texas A&M University-College Station, where he directs the Center for Geospatial Sciences, Applications, and Technology. Dr Ye received his Ph.D. in Geography from the University of California-Santa Barbara and San Diego State University in 2010. He is a Fellow of the American Association of Geographers and a Fellow of the Royal Geographical Society.
Dr Xinyue Ye is the Harold L. Adams Endowed Professor in the Department of Landscape Architecture & Urban Planning, Department of Geography, and Department of Computer Science & Engineering at Texas A&M University-College Station, where he directs the Center for Geospatial Sciences, Applications, and Technology. Dr Ye received his Ph.D. in Geography from the University of California-Santa Barbara and San Diego State University in 2010. He is a Fellow of the American Association of Geographers and a Fellow of the Royal Geographical Society.
Content
Introduction. Set up a Free Cloud-based Learning Environment. Introduction to Python Programming and Data Analytics. Data Collection and Storage. Data Process and Query. Data Visualization. Conclusion.