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.

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.

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.