Mastering Microsoft Fabric Unified Data Engineering Governance And Artificial Intelligence In The Cloud
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Mastering Microsoft Fabric: Unified Data Engineering, Governance, and Artificial Intelligence in the Cloud
The development of cloud platforms has changed how organizations manage data, implement governance, and incorporate artificial intelligence into business processes. Microsoft Fabric combines data engineering, governance, real-time analytics, and AI into a single, scalable ecosystem. This book, Mastering Microsoft Fabric: Unified Data Engineering, Governance, and AI in the Cloud, is designed for professionals, researchers, and architects interested in Microsoft Fabric. It covers real-world use cases, architectural patterns, and practical implementations, this guide explores how to build modern, governed, and intelligent data systems that meet the demands of today’s dynamic digital environments. Drawing on extensive experience in databases, cybersecurity, and AI, I have written this book to address the divide between theoretical concept and practical implementation. This work focuses on role- and rule-based access control, multi-tenant data governance, AI integration, and secure data pipelines, all critical pillars in modern enterprise architecture. This book functions as both a technical guide and a strategic reference, outlining how Microsoft Fabric is influencing cloud-native data engineering and decision-making. It aims to inform readers about compliance focused architectures and servers as a resource for professionals working within cloud-first and AI-driven environments.
Deep Learning with Azure
Get up-to-speed with Microsoft's AI Platform. Learn to innovate and accelerate with open and powerful tools and services that bring artificial intelligence to every data scientist and developer. Artificial Intelligence (AI) is the new normal. Innovations in deep learning algorithms and hardware are happening at a rapid pace. It is no longer a question of should I build AI into my business, but more about where do I begin and how do I get started with AI?Written by expert data scientists at Microsoft, Deep Learning with the Microsoft AI Platform helps you with the how-to of doing deep learning on Azure and leveraging deep learning to create innovative and intelligent solutions. Benefit from guidance on where to begin your AI adventure, and learn how the cloud provides you with all the tools, infrastructure, and services you need to do AI. What You'll LearnBecome familiar with the tools, infrastructure, and services available for deep learning on Microsoft Azure such as Azure Machine Learning services and Batch AIUse pre-built AI capabilities (Computer Vision, OCR, gender, emotion, landmark detection, and more)Understand the common deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs) with sample code and understand how the field is evolvingDiscover the options for training and operationalizing deep learning models on Azure Who This Book Is ForProfessional data scientists who are interested in learning more about deep learning and how to use the Microsoft AI platform. Some experience with Python is helpful.
Mastering Cloud Computing
Mastering Cloud Computing is designed for undergraduate students learning to develop cloud computing applications. Tomorrow's applications won't live on a single computer but will be deployed from and reside on a virtual server, accessible anywhere, any time. Tomorrow's application developers need to understand the requirements of building apps for these virtual systems, including concurrent programming, high-performance computing, and data-intensive systems. The book introduces the principles of distributed and parallel computing underlying cloud architectures and specifically focuses on virtualization, thread programming, task programming, and map-reduce programming. There are examples demonstrating all of these and more, with exercises and labs throughout. - Explains how to make design choices and tradeoffs to consider when building applications to run in a virtual cloud environment - Real-world case studies include scientific, business, and energy-efficiency considerations