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Business --- Information resources management. --- Data processing. --- Corporations --- Information resource management --- Information systems management --- IRM (Information resources management) --- Management --- Management information systems --- Electronic data processing --- Information resources management

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Knowledge Engineering (KE) is a fi eld within artifi cial intelligence that develops knowledgebased systems. KE is the process of imitating how a human expert in a specifi c domain would act and take decisions. It contains large amounts of knowledge, like metadata and information about a data object that describes characteristics such as content, quality, and format, structure and processes. Such systems are computer programs that are the basis of how a decision is made or a conclusion is reached. It is having all the rules and reasoning mechanisms to provide solutions to real-world problems. This book presents an extensive collection of the recent fi ndings and innovative research in the information system and KE domain. Highlighting the challenges and diffi culties in implementing these approaches, this book is a critical reference source for academicians, professionals, engineers, technology designers, analysts, undergraduate and postgraduate students in computing science and related disciplines such as Information systems, Knowledge Engineering, Intelligent Systems, Artifi cial Intelligence, Cognitive Neuro - science, and Robotics. In addition, anyone who is interested or involved in sophisticated information systems and knowledge engineering developments will fi nd this book a valuable source of ideas and guidance.

Information resources management. --- Information resources management --- Corporations --- Information resource management --- Information systems management --- IRM (Information resources management) --- Management --- Management information systems --- Security measures.

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Dr Viktor Dörfler combines his background in developing and implementing AI with scholarly research on knowledge and cultivating talent to address misconceptions about AI. The Element explains what AI can and cannot do, carefully delineating facts from beliefs or wishful thinking. Filled with examples, this practical Element provokes thinking. The purpose is to help CEOs figure out how to make the best use of AI, suggesting how to extract AI's greatest value through appropriate task allocation between human experts and AI. The author challenges the attribution of characteristics like understanding, thinking, and creativity to AI, supporting his argument with the ideas of the finest AI philosophers. He also discusses in depth one of the most sensitive AI-related topics: ethics. The readers are encouraged to make up their own minds about AI and draw their own conclusions rather than accepting opinions from people with vested interests or an agenda.

Artificial intelligence --- Financial services industry --- Finance --- Business --- Information resources management. --- Financial applications. --- Information technology. --- Technological innovations. --- Data processing. --- Economics --- Currency question --- Funding --- Funds --- Service industries --- Services, Financial --- Management --- Management information systems --- Corporations --- Information resource management --- Information systems management --- IRM (Information resources management) --- Electronic data processing --- Data processing --- Information resources management

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Information resources management. --- Computer systems. --- Information technology. --- IT (Information technology) --- Technology --- Telematics --- Information superhighway --- Knowledge management --- ADP systems (Computer systems) --- Computing systems --- Systems, Computer --- Electronic systems --- Cyberinfrastructure --- Corporations --- Information resource management --- Information systems management --- IRM (Information resources management) --- Management --- Management information systems --- Information resources management

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Learn to deploy simple and complex applications that are beyond the scope of default Intune application deployment scenarios and limitations. This book will help you deploy applications using a PowerShell script. The book starts with PowerShell Cmdlets to get an understanding of deployment through PowerShell scripts. Next, you will learn how to work with msiexec where you will learn which properties of your MSI can be set and what values can be passed to them, even if you do not know what the properties and values initially are. Further, you will learn how to install and uninstall a Setup.exe and how to determine the silent switches, along with MSI extraction methods. You will then learn detection rules using PowerShell, including how to detect by registry or application version and build numbers as well as using custom PowerShell detection rules. You will then gain an understanding of the location to run the script. Moving forward, you will go through installing a program by calling MSI or Setup.exe using PowerShell and how to handle spaces in the filenames. Following this, you will go through how to deploy the various script types in Intune; whether it is a standard script, or if the whole script is a function or contains functions, or if it has an entry point. Deployment Templates and application preparation in Intune are discussed next, along with the process to create the .Intunewin with the Intune Winapp Util. You will then learn how to uninstall previous applications before a new deployment. You'll also be walked through useful snippets and examples of deployment where you will be able to utilize all the aspects of deployment in Intune discussed in prior chapters. After reading the book, you will be able to manage application deployments and detection rules using PowerShell with Microsoft Intune. What You Will Learn: How to find valid properties and values to use with msiexec Using PowerShell for detection rule Deploying using a template for reliable and repeatable deployments How to create the Windows App (Win32) App Who Is This Book For: I.T Professionals who manage application deployments using Microsoft Intune.

Electronic data processing --- Information resources management. --- Business --- Application software. --- Management --- Distributed processing. --- Data processing. --- Distributed computer systems in electronic data processing --- Distributed computing --- Distributed processing in electronic data processing --- Computer networks --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Corporations --- Information resource management --- Information systems management --- IRM (Information resources management) --- Management information systems --- Information resources management