Martin Oberhofer – författare

Architecture for the Intelligent Enterprise: Powerful New Ways to Maximize the Real-time Value of Information

 

Tomorrow’s winning “Intelligent Enterprises” will bring together far more diverse sources of data, analyze it in more powerful ways, and deliver immediate insight to decision-makers throughout the organization. Today, however, most companies fail to apply the information they already have, while struggling with the complexity and costs of their existing information environments.

 

In this book, a team of IBM’s leading information management experts guide you on a journey that will take you from where you are today toward becoming an “Intelligent Enterprise.”

 

Drawing on their extensive experience working with enterprise clients, the authors present a new, information-centric approach to architecture and powerful new models that will benefit any organization. Using these strategies and models, companies can systematically unlock the business value of information by delivering actionable, real-time information in context to enable better decision-making throughout the enterprise–from the “shop floor” to the “top floor.”

 

Coverage Includes

Highlighting the importance of Dynamic Warehousing Defining your Enterprise Information Architecture from conceptual, logical, component, and operational views Using information architecture principles to integrate and rationalize your IT investments, from Cloud Computing to Information Service Lifecycle Management Applying enterprise Master Data Management (MDM) to bolster business functions, ranging from compliance and risk management to marketing and product management Implementing more effective business intelligence and business performance optimization, governance, and security systems and processes Understanding “Information as a Service” and “Info 2.0,” the information delivery side of Web 2.0

The International Commission on Radiological Protection and the Euratom Council directive have specified that workers exposed to ionizing radiation shall be subjected to individual dose monitoring. In the past, individual doses have almost always been monitored by film badge dosimeter, but thermoluminescent dosimeters (TLDs) are now coming into widespread use, principally due to the availability of automated readout systems. This work gives details of the operation of and experience gained with a number of large-scale TL personnel dosimetry services, with particular reference to the management aspects of such services. It should be of interest to technical and administrative personnel in TLD services, TLD system designers, staff of licensing authorities concerned with dosimetric licensing and students of radiation protection, especially in the area of protection from ionizing radiation. A basic knowledge of atomic and nuclear physics is assumed, and a training in radiation protection or health physics would be an advantage.

Your company has committed to AI. Congratulations, now what? This practical book offers a holistic plan for implementing AI from the perspective of IT and IT operations in the enterprise. You will learn about AI’s capabilities, potential, limitations, and challenges. This book teaches you about the role of AI in the context of well-established areas, such as design thinking and DevOps, governance and change management, blockchain, and quantum computing, and discusses the convergence of AI in these key areas of the enterprise.Deploying AI in the Enterprise provides guidance and methods to effectively deploy and operationalize sustainable AI solutions. You will learn about deployment challenges, such as AI operationalization issues and roadblocks when it comes to turning insight into actionable predictions. You also will learn how to recognize the key components of AI information architecture, and its role in enabling successful and sustainable AI deployments.And you will come away with an understanding of how to effectively leverage AI to augment usage of core information in Master Data Management (MDM) solutions.What You Will LearnUnderstand the most important AI concepts, including machine learning and deep learningFollow best practices and methods to successfully deploy and operationalize AI solutionsIdentify critical components of AI information architecture and the importance of having a planIntegrate AI into existing initiatives within an organizationRecognize current limitations of AI, and how this could impact your businessBuild awareness about important and timely AI researchAdjust your mindset to consider AI from a holistic standpointGet acquainted with AI opportunities that exist in various industriesWho This Book Is ForIT pros, data scientists, and architects who need to address deployment and operational challenges related to AI and need a comprehensive overview on how AI impacts other business critical areas. It is not an introduction, but is for the reader who is looking for examples on how to leverage data to derive actionable insight and predictions, and needs to understand and factor in the current risks and limitations of AI and what it means in an industry-relevant context.

Your company has committed to AI. Congratulations, now what? This practical book offers a holistic plan for implementing AI from the perspective of IT and IT operations in the enterprise. You will learn about AI’s capabilities, potential, limitations, and challenges. This book teaches you about the role of AI in the context of well-established areas, such as design thinking and DevOps, governance and change management, blockchain, and quantum computing, and discusses the convergence of AI in these key areas of the enterprise.Deploying AI in the Enterprise provides guidance and methods to effectively deploy and operationalize sustainable AI solutions. You will learn about deployment challenges, such as AI operationalization issues and roadblocks when it comes to turning insight into actionable predictions. You also will learn how to recognize the key components of AI information architecture, and its role in enabling successful and sustainable AI deployments.And you will come away with an understanding of how to effectively leverage AI to augment usage of core information in Master Data Management (MDM) solutions.What You Will LearnUnderstand the most important AI concepts, including machine learning and deep learningFollow best practices and methods to successfully deploy and operationalize AI solutionsIdentify critical components of AI information architecture and the importance of having a planIntegrate AI into existing initiatives within an organizationRecognize current limitations of AI, and how this could impact your businessBuild awareness about important and timely AI researchAdjust your mindset to consider AI from a holistic standpointGet acquainted with AI opportunities that exist in various industriesWho This Book Is ForIT pros, data scientists, and architects who need to address deployment and operational challenges related to AI and need a comprehensive overview on how AI impacts other business critical areas. It is not an introduction, but is for the reader who is looking for examples on how to leverage data to derive actionable insight and predictions, and needs to understand and factor in the current risks and limitations of AI and what it means in an industry-relevant context. 

Ihr Unternehmen hat sich für KI entschieden. Glückwunsch, was nun? Dieses praktische Buch bietet einen ganzheitlichen Plan für die Implementierung von KI aus der Perspektive der IT und des IT-Betriebs im Unternehmen. Sie erfahren etwas über die Fähigkeiten, das Potenzial, die Grenzen und die Herausforderungen von KI. In diesem Buch erfahren Sie, welche Rolle KI im Kontext etablierter Bereiche wie Design Thinking und DevOps, Governance und Change Management, Blockchain und Quantum Computing spielt, und diskutieren die Konvergenz von KI in diesen Schlüsselbereichen des Unternehmens.Deploying AI in the Enterprise bietet Anleitungen und Methoden zur effektiven Bereitstellung und Operationalisierung nachhaltiger KI-Lösungen. Sie lernen die Herausforderungen bei der Implementierung kennen, wie z. B. Probleme bei der KI-Operationalisierung und Hindernisse bei der Umsetzung von Erkenntnissen in umsetzbare Prognosen. Sie werden auch lernen, wie Sie die Schlüsselkomponenten der KI-Informationsarchitektur erkennen und welche Rolle sie für eine erfolgreiche und nachhaltige KI-Implementierung spielt. Und Sie werden verstehen, wie Sie KI effektiv einsetzen können, um die Nutzung von Kerninformationen in Master Data Management (MDM)-Lösungen zu verbessern.Was Sie lernen werdenVerstehen der wichtigsten KI-Konzepte, einschließlich maschinelles Lernen und Deep LearningBefolgen von Best Practices und Methoden zur erfolgreichen Bereitstellung und Operationalisierung von KI-LösungenErkennen der kritischen Komponenten der KI-Informationsarchitektur und der Bedeutung eines PlansIntegration von KI in bestehende Initiativen innerhalb einer OrganisationErkennen der aktuellen Grenzen von KI und wie sich dies auf Ihr Unternehmen auswirken könnteBewusstsein für wichtige und aktuelle KI-Forschung schaffenIhre Denkweise anpassen, um KI von einem ganzheitlichen Standpunkt aus zu betrachtenMachen Sie sich mit den Möglichkeiten von KI in verschiedenen Branchen vertraut.Für wen ist dieses Buch gedacht?IT-Profis, Datenwissenschaftler und Architekten, die sich mit den Herausforderungen bei der Implementierung und dem Betrieb von KI auseinandersetzen müssen und einen umfassenden Überblick darüber benötigen, wie sich KI auf andere geschäftskritische Bereiche auswirkt. Es ist keine Einführung, sondern richtet sich an Leser, die nach Beispielen für die Nutzung von Daten suchen, um daraus verwertbare Erkenntnisse und Vorhersagen abzuleiten, und die die aktuellen Risiken und Grenzen von KI verstehen und berücksichtigen müssen und wissen wollen, was dies in einem branchenrelevanten Kontext bedeutet.