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Shiyan Xu: Apache Hudi - The Definitive
Guide

Apache Hudi - The Definitive Guide

Building Robust, Open, and High-Performing Data Lakehouses

Tableau at Work is the perfect book for anyone who wants a comprehensive guide and reference to Tableau, from beginners and novices all the way to advanced and professional users.

Tableau at Work

Customer Relationship Management in the Digital Age charts the concepts, strategies, benefits, and technologies of CRM in an evolving and increasingly digital business landscape. It empowers readers to use CRM to forge enduring customer connections, optimize experiences, and drive loyalty across diverse industries and markets.

Customer Relationship Management in the Digital Age

Written by a data scientist with decades of practical experience on some of the most challenging datasets, this book caters to both novices and professionals working in the fields of data science and machine learning. It enables novices to enter these fields with confidence and ease. There are no formal prerequisites. An introduction to Python is included. The book then proceeds to cover some of the language's most advanced features. The mathematical foundations that follow are meticulously explained. The discussion then proceeds to a practical consideration of data science and machine learning. The material is delivered through case studies developed on real datasets. The reader is invited to follow these case studies, and so develop experience in working with real data. Numerous solved exercises make this work suitable for self-study. The contents of this book have been taught by the author to students of different age groups and levels of experience at Imperial College London and at the Thalesians Intensive Summer School in Artificial Intelligence over the years.

Python, Data Science And Machine Learning: From Scratch To Productivity

Quantum Computing: Principles and Paradigms covers a broad range of topics, providing a state-of-the-art and comprehensive reference for the rapid progress in the field of quantum computing and related technologies from major international companies (such as IBM, Google, Intel, Rigetti, Q-Control) and academic researchers. This book appeals to a broad readership, as it covers comprehensive topics in the field of quantum computing, including hardware, software, algorithms, and applications, with chapters written by both academic researchers and industry developers. This book presents readers with the fundamental concepts of quantum computing research, along with the challenges involved in developing practical devices and applications.

Principles and Paradigms

Quantum Computing

The Internet of Things (IoT) has revolutionized the way we live, work, and interact with our surroundings. Sensor systems play a crucial role in these technological advancements, and their integration with IoT has revolutionized the way data is acquired, processed, and utilized. This book offers a structured understanding of sensor technologies, principles, applications, and their integration into IoT systems, thereby bridging the gap between sensors and IoT applications.This book goes beyond theoretical explanations and stands out as a comprehensive and practical guide with a strong focus on real-world applications. It reveals some interesting aspects of such fascinating interactions between sensors and the IoT -- in particular, cutting-edge technologies and possibilities ranging from smart homes to industrial automation and beyond. It also offers a detailed exploration of sensors and the measurement principles characteristic of sensors designed to detect and measure specific environmental parameters -- especially those equipped with the capability to convert the collected data into electronic signals, which can then be processed and communicated to other connected devices through the internet. Data-based innovation in driving technological advancements is also addressed, and Intellectual Property (IP) is explored as a key element in bridging the gap between scientific research and marketable products.This book is an indispensable guide for students, researchers, and professionals alike. Its comprehensive approach to sensor technology makes it a valuable resource for scientists, engineers, and decision makers in industry.

Sensors And The Internet Of Things: Acquisition And Use Of Big Data

Learn to build a web app that can monitor millions of posts across all social media platforms to chart public opinion in real time. Social media has become our modern-day agora, the place where we get our news and engage in political discourse. With disinformation, hate speech, foreign interference, authoritarianism, market monopolization, and political polarization all on the rise, monitoring social media in the public interest has never been so difficult nor so urgent. Social Media Observatory is an in-depth beginner’s guide to coding full-stack web applications in Python to track and analyze social media activity at scale, giving you unparalleled insights into the cultural and political conversations of our time, then empowering you to reach your own conclusions. You’ll start by coding a web app to monitor Russian disinformation channels discussing Ukraine on Telegram, then learn more adversarial methods to scrape the Wayback Machine, Instagram, and TikTok. You’ll detect Twitter bots following Saudi influencers, extract text-embedded URLs to reveal a white supremacist blogosphere, parse archived tweets to reveal the discourse leading up to the January 6 insurrection, and learn to circumvent Meta's and ByteDance's defenses to scrape Instagram and TikTok, collecting evidence of war crimes in the Middle East. Finally, you’ll write an API and deploy your observatory to a cloud server to collaborate with other investigators. By the end of the book, you’ll have a working website that allows collaborators to log in, request data collection, and perform analysis of collected data, via a point-and-click interface.&nbsp; Along the way, you’ll learn to: <ul><li>Use Python and RabbitMQ to retrieve Telegram data from a remote API</li><li>Store data with PostgreSQL and query it with SQLAlchemy</li><li>Analyze the data you’ve retrieved with Pandas, NetworkX, Gephi, and other tools</li><li>Use state-of-the-art AI tools to transcribe audio and classify text</li><li>Deploy a website with an interactive dashboard using FastAPI, Dash, Cytoscape, Uvicorn, Gunicorn, Nginx, AWS, and Let’s Encrypt</li><li>Containerize your apps with Docker and provision infrastructure with Pulumi</li></ul> Whether you’re a citizen scientist, a security researcher, a journalist, an activist, or a scholar, Social Media Observatory is an essential blueprint for building your window into online worlds.

Learn to build a web app that can monitor millions of posts across all social media platforms to chart public opinion in real time. Social media has become our modern-day agora, the place where we get our news and engage in political discourse. With disinformation, hate speech, foreign interference, authoritarianism, market monopolization, and political polarization all on the rise, monitoring social media in the public interest has never been so difficult nor so urgent. Social Media Observatory is an in-depth beginner’s guide to coding full-stack web applications in Python to track and analyze social media activity at scale, giving you unparalleled insights into the cultural and political conversations of our time, then empowering you to reach your own conclusions. You’ll start by coding a web app to monitor Russian disinformation channels discussing Ukraine on Telegram, then learn more adversarial methods to scrape the Wayback Machine, Instagram, and TikTok. You’ll detect Twitter bots following Saudi influencers, extract text-embedded URLs to reveal a white supremacist blogosphere, parse archived tweets to reveal the discourse leading up to the January 6 insurrection, and learn to circumvent Meta's and ByteDance's defenses to scrape Instagram and TikTok, collecting evidence of war crimes in the Middle East. Finally, you’ll write an API and deploy your observatory to a cloud server to collaborate with other investigators. By the end of the book, you’ll have a working website that allows collaborators to log in, request data collection, and perform analysis of collected data, via a point-and-click interface.&nbsp; Along the way, you’ll learn to: <ul><li>Use Python and RabbitMQ to retrieve Telegram data from a remote API</li><li>Store data with PostgreSQL and query it with SQLAlchemy</li><li>Analyze the data you’ve retrieved with Pandas, NetworkX, Gephi, and other tools</li><li>Use state-of-the-art AI tools to transcribe audio and classify text</li><li>Deploy a website with an interactive dashboard using FastAPI, Dash, Cytoscape, Uvicorn, Gunicorn, Nginx, AWS, and Let’s Encrypt</li><li>Containerize your apps with Docker and provision infrastructure with Pulumi</li></ul> Whether you’re a citizen scientist, a security researcher, a journalist, an activist, or a scholar, Social Media Observatory is an essential blueprint for building your window into online worlds.

Social Media Observatory

Sybex Study Guide

Your complete Guide to preparing for the AWS® Certified Data Engineer: Associate exam The AWS® Certified Data Engineer Study Guide is your one-stop resource for complete coverage of the challenging DEA-C01 Associate exam. This Sybex Study Guide covers 100% of the DEA-C01 objectives. Prepare for the exam faster and smarter with Sybex thanks to accurate content including, an assessment test that validates and measures exam readiness, real-world examples and scenarios, practical exercises, and challenging chapter review questions. Reinforce and retain what you've learned with the Sybex online learning environment and test bank, accessible across multiple devices. Get ready for the AWS Certified Data Engineer exam - quickly and efficiently - with Sybex. Coverage of 100% of all exam objectives in this Study Guide means you'll be ready for: <ul><li>Data Ingestion and Transformation</li><li>Data Store Management</li><li>Data Operations and Support</li><li>Data Security and Governance</li></ul> ABOUT THE AWS DATA ENGINEER - ASSOCIATE CERTIFICATION The AWS Data Engineer - Associate certification validates skills and knowledge in core data-related Amazon Web Services. It recognizes your ability to implement data pipelines and to monitor, troubleshoot, and optimize cost and performance issues in accordance with best practices Interactive learning environment Take your exam prep to the next level with Sybex's superior interactive online study tools. To access our learning environment, simply visit www.wiley.com/go/sybextestprep, register your book to receive your unique PIN, and instantly gain one year of FREE access after activation to: ¿ Interactive test bank with 5 practice exams to help you identify areas where further review is needed. Get more than 90% of the answers correct, and you're ready to take the certification exam. ¿ 100 electronic flashcards to reinforce learning and last-minute prep before the exam ¿ Comprehensive glossary in PDF format gives you instant access to the key terms so you are fully prepared

Associate (DEA-C01) Exam

AWS Certified Data Engineer Study Guide

"Harnessing the power of data and AI methods to tackle complex societal challenges requires transdisciplinary collaboration across academia, industry, and government. This compelling book offers a blueprint for researchers, professionals, and institutions wanting to use innovative, holistic, data-driven methods to solve problems of societal value"--

Harnessing the power of data and AI methods to tackle complex societal challenges requires transdisciplinary collaboration across academia, industry, and government. This compelling book offers a blueprint for researchers, professionals, and institutions wanting to use innovative, holistic, data-driven methods to solve problems of societal value.

Harnessing AI for Societal Good

Data, Systems, and Society

Use this step-by-step guide to prepare, design and implement a simplified data governance programme built to meet the needs of your organization. Prepare, design and implement a data governance framework that works for your organization with this practical guide to harnessing data successfully.

Design a Framework that Works for Your Organization

Effective Data Governance

Chapman and Hall/CRC Series on Statistics in Business and Economics

This book examines under what circumstances, and with which techniques, one can reasonably infer cause and effect in a business setting, and use the insight to drive business decisions. It is written at a level accessible to anyone with a master's degree in analytics, business, economics, statistics, computer science, or a related field.

This book examines under what circumstances, and with which techniques, one can reasonably infer cause and effect in a business setting, and use the insight to drive business decisions. It is written at a level accessible to anyone with a master’s degree in analytics, business, economics, statistics, computer science, or a related field.

Cause and Effect Business Analytics and Data Science

Mathematical Modelling for Big Data Analytics is a comprehensive guidebook that explores the use of mathematical models and algorithms for analyzing large and complex datasets. The book covers a range of topics, including statistical modeling, machine learning, optimization techniques, and data visualization, and provides practical examples and case studies to demonstrate their applications in real-world scenarios. Users will find a clear and accessible resource to enhance their skills in mathematical modeling and data analysis for big data analytics. Real-world examples and case studies demonstrate how to approach and solve complex data analysis problems using mathematical modeling techniques. This book will help readers understand how to translate mathematical models and algorithms into practical solutions for real-world problems. Coverage of the theoretical foundations of big data analytics, including qualitative and quantitative analytics techniques, digital twins, machine learning, deep learning, optimization, and visualization techniques make this a must have resource.

Mathematical Modeling for Big Data Analytics

Apache Hudi - The Definitive Guide

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