Microsoft programming Books

Book SynopsisBuild your first digital twin MVP and gain first-hand experience of using the technology, the challenges it presents, and its impact on your organizationKey Features Create a digital twin prototype using Microsoft Azure Digital Twin Explore the digital twin approach to the design, operations, and maintenance of industrial assets and products Understand key characteristics and components of a digital twin through practical use cases and business scenarios Book DescriptionDigital twin technology enables organizations to create digital representations of physical entities such as assets, systems, and processes throughout their life cycle. It improves asset performance, utilization, and safe operations and reduces manufacturing, operational, and maintenance costs. The book begins by introducing you to the concept of digital twins and sets you on a path to develop a digital twin strategy to positively influence business outcomes in your organization. You'll understand how digital twins relate to physical assets, processes, and technology and learn about the prerequisite conditions for the right platform, scale, and use case of your digital twins. You'll then get hands-on with Microsoft's Azure Digital Twins platform for your digital twin development and deployment. The book equips you with the knowledge to evaluate enterprise and specialty platforms, including the cloud and industrial IoT required to set up your digital twin prototype. Once you've built your prototype, you'll be able to test and validate it relative to the intended purpose of the twin through pilot deployment, full deployment, and value tracking techniques. By the end of this book, you'll have developed the skills to build and deploy your digital twin prototype, or minimum viable twin, to demonstrate, assess, and monitor your asset at specific stages in the asset life cycle.What you will learn Identify key criteria for the applicability of digital twins in your organization Explore the RACI matrix and rapid experimentation for choosing the right tech stack for your digital twin system Evaluate public cloud, industrial IoT, and enterprise platforms to set up your prototype Develop a digital twin prototype and validate it using a unit test, integration test, and functional test Perform an RoI analysis of your digital twin to determine its economic viability for the business Discover techniques to improve your digital twin for future enhancements Who this book is forThe digital twin book is for mid-career subject experts, including engineers and operations managers, building their first prototype (MVP) using digital twin technology. The book will help professionals responsible for mechanical, process, and reliability engineering domains. You don't have to be a developer or programmer, but beginner-level programming skills will be helpful.Table of ContentsTable of Contents Introduction to Digital Twin Planning Your Digital Twin Identifying the First Digital Twin Getting Started with Our First Digital Twin Setting Up a Digital Twin Prototype Building the Digital Twin Prototype Deployment and Value Tracking Enhancing the Digital Twin

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Book SynopsisPart I: Modelling and the Income Statement.- Chapter 1: What is an income statement semantic model?.- Chapter 2: How to Construct an Income Statement.- Chapter 3: Building a Reusable Solution.- Chapter 4: Why model the income statement?.- Part II: Calculating Account Balances - Chapter 5: Conceptual Account Balance Models.- Chapter 6: Logical Account Balance Models.- Chapter 7: The Trial Balance Semantic Model.- Chapter 8: A Journal Entry Semantic Model.- Part III: Producing External Income Statement Semantic Models.- Chapter 9: The Four Subtotal and Subset Types.- Chapter 10: External Reporting Logical Models.- Chapter 11: External Reporting Semantic Models.- Part IV: Producing Internal Income Statement Sematic Models.- Chapter 12: Internal Reporting Logical Models.- Chapter 13: Internal Reporting Semantic Models.- Chapter 14: Security and Self-service Considerations.- Chapter 15: Review of the Sixteen Challenges.

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Book SynopsisChapter 1: An Introduction to Chat and Generative AI.- Chapter 2: An Introduction to Microsoft Copilot.- Chapter 3: A (Brief) Introduction to Responsible AI.- Chapter 4: Accessing Copilot.- Chapter 5: Copilot in Word.- Chapter 6: Copilot in Excel.- Chapter 7: Copilot in PowerPoint.- Chapter 8: Copilot in Outlook.- Chapter 9: Copilot in Teams.- Chapter 10: Copilot in Microsoft Graph-Grounded Chat.- Chapter 11: A (Brief) Talk About Copilot in the Microsoft Ecosystem.

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Book SynopsisUnderstand .NET memory management internal workings, pitfalls, and techniques in order to effectively avoid a wide range of performance and scalability problems in your software. Despite automatic memory management in .NET, there are many advantages to be found in understanding how .NET memory works and how you can best write software that interacts with it efficiently and effectively. This book is your comprehensive guide to writing better software by understanding and working with memory management in .NET, from Framework up to .NET 8. Thoroughly vetted by the .NET Team at Microsoft, this book contains valuable troubleshooting scenarios designed to help diagnose challenging memory problems. You will also benefit from a multitude of .NET memory management rules to live by that introduce methods for writing memory-aware code and the means for avoiding common, destructive pitfalls. What You'll LearnUnderstand the theoretical underpinnings of automatic memory managementTake a deep dive into every aspect of .NET memory management, including detailed coverage of garbage collection (GC) implementation, that would otherwise take years of experience to acquireGet practical advice on how this knowledge can be applied in real-world software developmentUse practical knowledge of tools related to .NET memory management to diagnose various memory-related issuesExplore various aspects of advanced memory management, including use of Span and Memory typesWho This Book Is For.NET developers, solution architects, and performance engineers

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