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Gesamtkatalog

Catalogue complet

Business Analytics in Practice

Blockchain Analytics for Practitioners

Bridging Theory and Practice

Certification Study Companion Series

As organizations increasingly leverage Microsoft Fabric to unify their data engineering, analytics, and governance strategies, the role of the Fabric Analytics Engineer has become more crucial than ever. This book equips readers with the knowledge and hands-on skills required to excel in this domain and pass the DP-600 certification exam confidently.This book covers the entire certification syllabus with clarity and depth, beginning with an overview of Microsoft Fabric. You will gain an understanding of the platform’s architecture and how it integrates with data and AI workloads to provide a unified analytics solution. You will then delve into implementing a data warehouse in Microsoft Fabric, exploring techniques to ingest, transform, and store data efficiently. Next, you will learn how to work with semantic models in Microsoft Fabric, enabling them to create intuitive, meaningful data representations for visualization and reporting. Then, you will focus on administration and governance in Microsoft Fabric, emphasizing best practices for security, compliance, and efficient management of analytics solutions. Lastly, you will find detailed practice tests and exam strategies along with supplementary materials to reinforce key concepts.After reading the book, you will have the background and capability to learn the skills and concepts necessary both to pass the DP-600 exam and become a confident Fabric Analytics Engineer.What You Will Learn<ul><li>A complete understanding of all DP-600 certification exam objectives and requirements</li><li>Key concepts and terminology related to Microsoft Fabric Analytics</li><li>Step-by-step preparation for successfully passing the DP-600 certification exam</li><li>Insights into exam structure, question patterns, and strategies for tackling challenging sections</li><li>Confidence in demonstrating skills validated by the Microsoft Certified: Fabric Analytics Engineer Associate credential</li></ul>

Preparation for DP-600 Microsoft Certification

Microsoft Fabric Analytics Engineer Associate Certification Companion

Sustainable Development Goals Series

Research Insights from the Coronavirus

The COVID Information Commons

Springer Texts in Social Sciences

This book is designed as a foundational textbook for upper-level undergraduate and graduate students from non-technical fields who want to acquire a basic understanding of data science and learn practical skills in data analysis. It distinguishes itself by combining theoretical knowledge with practical applications, bridged through extensive Python programming exercises. To accommodate social scientists' needs, the book emphasizes the analysis of textual data, especially those acquired from surveys and social media. For those without prior programming experience, the book provides instruction on using an AI-assisted Python programming tool, following the learn-by-doing methodology of acquiring new skills through experience. The overall learning goal of the book is to develop a conceptual understanding of data mining as well as the technical skills necessary for real-world data analysis.

Practical Data Mining with AI for Social Scientists

Is your company struggling to get real value from data? Problem solved. This book is your guide to transforming an organization from one that treats data as an afterthought or merely a support function into one that makes data a key driver of product development and business innovation. In doing so, you’ll be able to measure outcomes that matter, rather than just tracking features shipped.In a world where products are increasingly driven by data and AI, traditional approaches to product development and data management have become barriers to growth rather than enablers of success. At its core, this book establishes two fundamental principles for success: autonomous, outcome/data-driven product teams and the need for data assets to be managed as products. These principles are then expanded into practical frameworks, step-by-step implementation guides, and maturity models, that cross-functional teams in any industry can incorporate in their decision-making.Whether you're a product manager wanting to become more data-fluent, a data professional aiming to increase your product impact, or a leader trying to break down silos in your organization, Data as a Product Driver provides practical steps to transform how your company uses data. What You Will Learn:<ul><li>Reorganize your teams around business problems instead of technical disciplines.</li><li>Manage the transition from centralized data teams to domain-driven decentralized data ownership.</li><li>Build effective data platform teams that enable product teams while maintaining consistent standards across your data ecosystem.</li><li>Create data assets that provide lasting value across your organization.</li><li>Implement the right operating model for your company's size and maturity level.</li></ul>

Strategies for Aligning Data and Product Teams to Transform Organizations

Data as a Product Driver

Transform your data replication strategy into a competitive advantage with Oracle GoldenGate 23ai.
This comprehensive guide delivers the practical knowledge DBAs and architects need to implement, optimize, and scale Oracle GoldenGate 23ai in production environments. Written by Oracle ACE Director Bobby Curtis, it blends deep technical expertise with real-world business insights from hundreds of implementations across manufacturing, financial services, and technology sectors.
Beyond traditional replication, this book explores the groundbreaking capabilities that make GoldenGate 23ai essential for modern AI initiatives. Learn how to implement real-time vector replication for RAG systems, integrate with cloud platforms like GCP and Snowflake, and automate deployments using REST APIs and Python. Each chapter offers proven strategies to deliver measurable ROI while reducing operational risk.
Whether you're upgrading from Classic GoldenGate, deploying your first cloud data pipeline, or building AI-ready data architectures, this book provides the strategic guidance and technical depth to succeed. With Bobby's signature direct approach, you'll avoid common pitfalls and implement best practices that scale with your business.
What You Will Learn
<ul>
<li>Master the microservices architecture and new capabilities of Oracle GoldenGate 23ai</li>
<li>Implement secure, high-performance data replication across Oracle, PostgreSQL, and cloud databases</li>
<li>Configure vector replication for AI and machine learning workloads, including RAG systems</li>
<li>Design and build multi-master replication models with automatic conflict resolution</li>
<li>Automate deployments and management using RESTful APIs and Python</li>
<li>Optimize performance for sub-second replication lag in production environments</li>
<li>Secure your replication environment with enterprise-grade features and compliance</li>
<li>Upgrade from Classic to Microservices architecture with zero downtime</li>
<li>Integrate with cloud platforms including OCI, GCP, AWS, and Azure</li>
<li>Implement real-time data pipelines to BigQuery, Snowflake, and other cloud targets</li>
<li>Navigate Oracle licensing models and optimize costs</li>
</ul>
Who This Book Is For
Database administrators, architects, and IT leaders working with Oracle GoldenGate—whether deploying for the first time, migrating from Classic architecture, or enabling AI-driven replication—will find actionable guidance on implementation, performance tuning, automation, and cloud integration. Covers unidirectional and multi-master replication and is packed with real-world use cases.

Powering the Foundation of Data Integration and AI

Pro Oracle GoldenGate 23ai for the DBA

Zum Werk Das Handbuch bietet eine praxisbezogene und zugleich wissenschaftlich fundierte Darstellung der Rechtsfragen der Künstlichen Intelligenz und smarten Robotik. Es bietet nach Inkrafttreten der europäischen KI-Verordnung im August 2024 einen juristischen Gesamtüberblick hinsichtlich dieser sich dynamisch entwickelnden und zunehmend in den Fokus von Wirtschaft, Wissenschaft, Politik und breiter Öffentlichkeit rückenden Technologien. Das Handbuch untergliedert sich in einen Grundlagenteil zu technischen und regulatorischen Fragen, einen Abschnitt der sich mit den Implikationen von KI und Robotik für einzelne Rechtsgebiete befasst, sowie Kapiteln zu Anwendungsfällen. Inhalt<ul><li>Technische Grundlagen der Künstlichen Intelligenz und der Robotik</li><li>Regulierung, insbesondere KI-VO</li><li>Verantwortung</li><li>Vertragsrechtliche Fragestellungen</li><li>Zivilrechtliche Haftung für KI und smarte Robotik</li><li>Verbraucherrecht</li><li>Strafrechtliche Implikationen von KI und Robotik</li><li>Arbeitsrechtliche Probleme von KI und Robotik</li><li>KI im Urheber- und im Patentrecht</li><li>KI-spezifische datenschutzrechtliche Herausforderungen</li><li>KI-spezifische Rechtsfragen der Cyber-Sicherheit</li><li>KI im Gesellschaftsrecht</li><li>Kapitalmarkt- und Finanzdienstleistungsrecht</li><li>Versicherungsrecht</li><li>Wettbewerbsrecht</li><li>Telekommunikationsrecht</li><li>KI im Prozessrecht</li><li>Regierungs- und Verwaltungshandeln durch KI</li><li>KI und Steuerrecht</li><li>Anwendungsbeispiele, etwa Legal Tech, Vollautonomer Transport, Smart Devices &amp; Wearables, Personal Robots, Smart Contracts und Blockchain, Plattformen und KI, Verbrechensbekämpfung</li></ul> Zur Neuauflage Neu in der 2. Auflage:<ul><li>Einarbeitung der KI-VO</li><li>Neues Produktsicherheitsrecht</li><li>KI und Antidiskriminierungsrecht</li><li>KI und Geschäftsgeheimnisschutz</li><li>KI und Datenlizenzrecht</li><li>KI und Compliance</li><li>Neue Anwendungsfälle: ChatGPT, Smart Cities, Landwirtschaft, Tourismus</li></ul> Vorteile auf einen Blick<ul><li>KI-Compliance nach der neuen KI-VO</li><li>Lösungen für schwierige Anwendungsprobleme aus dem Bereich disruptiver Technologien</li><li>verständliche Darstellung technologischer/technischer Grundlagen</li><li>Antworten ausgewiesener Experten auf sich bereits jetzt oder sehr bald stellende Rechtsfragen von Unternehmen, Behörden, Anwaltskanzleien und Wissenschaft</li></ul> Zielgruppe Für Unternehmen und deren Syndikusanwaltschaft, Rechtsanwaltschaft, Behörden, Richterschaft und Wissenschaft jeglicher Disziplin, die sich mit den neuen Technologien befasst.

Rechtshandbuch

Künstliche Intelligenz und Robotik

Generative AI (Gen AI) represents a transformational technological shift by enabling the rapid creation of text, images, audio, and video through learning from vast amounts of human-generated data. Unlike traditional programming that relies on explicit instructions, Gen AI leverages machine learning to recognize patterns and generate content autonomously.SAP has embraced this revolution with its SAP BTP Generative AI Hub—a comprehensive platform designed to safely integrate generative AI and large language models into enterprise applications, with seamless support across its product suite including S/4 HANA, CRM, and HXM.This book provides a complete roadmap for understanding and applying these groundbreaking technologies. It begins by exploring the origins and core concepts of AI, deep learning, and transformer architectures, before delving into SAP’s AI Core and Generative AI Hub offerings. Through detailed, step-by-step examples, readers will learn to build enterprise use cases and discover the potential of Agentic AI for addressing real-world business challenges, making this a must-read for professionals seeking to drive innovation and efficiency in their organizations.&nbsp;You Will:<ul><li>Gain a solid understanding of artificial intelligence, deep learning, and transformer architectures, and how these concepts power generative AI.</li><li>Dive into SAP’s innovative AI offerings, exploring how the SAP BTP Generative AI Hub integrates generative AI and large language models safely into enterprise applications.</li><li>Understand how SAP’s generative AI capabilities are embedded across its product suite including S/4 HANA, CRM, and HXM.</li></ul>&nbsp;

SAP BTP Business AI Foundation and the Future of Business Applications

Building an Intelligent Enterprise with SAP Business AI

Information Security and Cryptography

[TO BE FINALISED] Lattice-based cryptography is a promising post-quantum cryptographic approach that can withstand potential attacks from future quantum computers. This book will introduce the theoretical mathematics that underpins lattice-based cryptography, such as the hard problems based on lattices upon which the security of lattice-based cryptosystems rely. It will provide examples of how these hard problems can be used to build basic lattice-based cryptographic primitives, namely encryption, digital signatures and key exchange, in addition to more advanced primitives such as identity-based encryption (IBE), attribute-based encryption (ABE) and hierarchical identity-based encryption (HIBE). Subsequently, the practical aspects of designing efficient and robust lattice-based cryptosystems in both hardware and software will be detailed. The resilience of lattice-based implementations to physical attacks will be discussed in addition to appropriate countermeasures that can be integrated into implementations to defend against such attacks. Finally, three case studies will be described to illustrate how lattice-based cryptography can be successfully embedded into real-world scenarios. <ul><li>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;Considers both the theory and practical aspects of lattice-based cryptography, which is a very promising post-quantum cryptographic approach</li><li>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;Provides a comprehensive theoretical overview of lattice-based cryptography detailing how to build both basic and advanced cryptographic primitives from lattice-based hard problems</li><li>&nbsp; &nbsp; &nbsp; &nbsp;&nbsp;Discusses practical implementation approaches for lattice-based cryptography for both hardware and software platforms</li><li>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Describes physical-attack resistant methodologies for lattice-based cryptography</li><li>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Describes how lattice-based cryptography can be utilized in practice and integrated into real-word scenarios, including applications requires real-time speeds (satellite communications) and resource constrained applications (IoT)</li></ul>







Assuming only&nbsp;basic knowledge of cryptography and the mathematics typically taught in undegraduate Computer Science, the book will appeal to scientists and researchers, lecturers and tutors, as well as to students studying the field and to practitioners and professionals looking to learn more about it.

From Theory to Practice

Lattice-Based Cryptography

Key Technologies on New Energy Vehicles

This book focuses on the current advanced technology field of battery operation big data and comprehensively describes the frontier technology of big data analysis and intelligent control of battery safe operation. The content systematically introduces the coupling mechanism of battery system safety and consistency, battery SOH estimation and prediction, battery safety state prediction, battery fault diagnosis, battery system risk pre-warning, and safety control strategy research.This book is suitable for teachers and students of universities and colleges in the automotive and related industries, engineers and technicians in the R&amp;D departments of enterprises or automotive enthusiasts to read and refer.The basis of English translation of this book, originally in Chinese, was facilitated by artificial intelligence. The content was later revised by the author for accuracy.

Big Data Analysis and Application of Power Battery Operation Safety

A Non-Technical Introduction in 30 Steps

Blockchain Basics

From Clicks to Code

Learn Data Science Using SAS Studio

This book introduces the concept of digital twins and their purposive usage, including the technology infrastructure and the method support necessary for their construction. The landscape of digital twins is illustrated through a range of use cases spread across different application domains such as strategy and business assessment in enterprises, logistics networks, manufacturing industries, chemical and refinery systems, sustainable food ecosystems, and public healthcare.&nbsp; All these examples show how digital twins are exploited to simulate complex scenarios depending on various external factors – all of which would not be feasible as real-world simulations because of their high costs, potential fatal damages, and unpredictable side effects.The book is written for professionals in industry who would like to learn about the application of these powerful methodologies and tools in various areas as well as for researchers in computer science who would like to draw inspirations for further development of this technology from real-world applications.

Digital Twins for Simulation-Based Decision-Making

Blockchain Analytics for Practitioners

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