As more and more industries are experiencing digital disruption, using information technology to enable a competitive advantage becomes a critical success factor for all enterprises. This book covers the authors' insights on how AI technologies can fundamentally reshape the IT services delivery lifecycle to deliver better business outcomes through a data-driven and knowledge-based approach. Three main challenges and the technologies to address them are discussed in detail: * Gaining actionable insight from operational data for service management automation and improved human decision making * Capturing and enhancing expert knowledge throughout the lifecycle from solution design to ongoing service improvement * Enabling self-service for service requests and problem resolution, through intuitive natural language interfaces The authors are top researchers and practitioners with deep experience in the fields of artificial intelligence and IT service management and are discussing both practical advice for IT teams and advanced research results. The topics appeal to CIOs and CTOs as well as researchers who want to understand the state of the art of applying artificial intelligence to a very complex problem space. Although the book is concise, it comprehensively discuss topics like gaining insight from operational data for automatic problem diagnosis and resolution as well as continuous service optimization, AI for solution design and conversational self-service systems.

Data Science, Big Data, and Artificial Intelligence are currently some of the most talked-about concepts in industry, government, and society, and yet also the most misunderstood. This book will clarify these concepts and provide you with practical knowledge to apply them. Featuring: - A comprehensive overview of the various fields of application of data science - Case studies from practice to make the described concepts tangible - Practical examples to help you carry out simple data analysis projects The book approaches the topic of data science from several sides. Crucially, it will show you how to build data platforms and apply data science tools and methods. Along the way, it will help you understand - and explain to various stakeholders - how to generate value from these techniques, such as applying data science to help organizations make faster decisions, reduce costs, and open up new markets. Furthermore, it will bring fundamental concepts related to data science to life, including statistics, mathematics, and legal considerations. Finally, the book outlines practical case studies that illustrate how knowledge generated from data is changing various industries over the long term. Contains these current issues: - Mathematics basics: Mathematics for Machine Learning to help you understand and utilize various ML algorithms. - Machine Learning: From statistical to neural and from Transformers and GPT-3 to AutoML, we introduce common frameworks for applying ML in practice - Natural Language Processing: Tools and techniques for gaining insights from text data and developing language technologies - Computer vision: How can we gain insights from images and videos with data science? - Modeling and Simulation: Model the behavior of complex systems, such as the spread of COVID-19, and do a What-If analysis covering different scenarios. - ML and AI in production: How to turn experimentation into a working data science product? - Presenting your results: Essential presentation techniques for data scientists Contributors: Stefan Papp / Wolfgang Weidinger / Katherine Munro / Bernhard Ortner / Annalisa Cadonna / Georg Langs / Roxane Licandro / Mario Meir-Huber / Danko Nikoli? / Zoltan Toth / Barbora Vesela / Rania Wazir / Günther Zauner

Die Verwendung standardisierter Kommunikationsprotokolle erlaubt den Fernzugriff auf Datenbanken auch in offenen Netzen, in denen Rechner unterschiedlicher Architektur (bezuglich der Hardware, der Betriebssysteme und der Datenbanksysteme) kooperieren. In dem Buch werden Kommunikationsfunktionen entwickelt fur einen dem Client/Server-Modell entsprechenden Datenbankzugriff in offenen Rechnernetzen (Remote Database Access - RDA). Zunachst werden bestehende Ansatze fur den Fernzugriff auf Datenbanken mit Hilfe eines geeigneten Modells klassifiziert. Dabei werden verteilte Datenbanksysteme, foderative Datenbanksysteme und verteilte Transaktionssysteme betrachtet. Der Entwurf der RDA-Kommunikationsfunktionen wird in die Verbindungsverwaltung, den Transfer von Datenbankoperationen, die Unterstutzung der Datenreprasentation und die Transaktionsverwaltung untergliedert. Als Schwerpunkt wird die Verwaltung verteilter Transaktionen in offenen Systemen behandelt. Da offene Systeme sich bezuglich ihrer Zuverlassigkeit unterscheiden konnen, werden in den hier eingefuhrten Transaktionsprotokollen sichere und unsichere Systeme modelliert. Fur sichere Systeme wird trotz der Beteiligung unsicherer Systeme eine konsistente Terminierung einer Transaktion in endlicher Zeit garantiert.