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Gesamtkatalog

Catalogue complet

Computer Science (R0)

Patrick C. K. Hung

Big Data Applications and Use Cases

Introduction to Big Data.- A Bloom Filter-based Approach for Supporting the Representation and Membership Query of Multidimensional Dataset.- Automatic Speech and Singing Discrimination for Audio Data Indexing.- Exploring the Feature Selection-based Data Analytics Solutions for Text Mining Online Communities by Investigating the Influential Factors - A Case Study of Programming CQA in Stack Overflow.- Temporal Event Tracing on Big Healthcare Data Analytics.- Unstructured Data, NoSQL, and Terms Analytics.- VLAB-C: Collaborative Virtual Laboratory in Cloud Computing and its Applications.- A Crowdsourcing Social Network Service for Social Enterprise Innovation.- Self-adaptive Parameters Optimization for Incremental Classification in Big Data Using Neural Network.- VLAB-C: Collaborative Virtual Laboratory in Cloud Computing and its Applications.- Case Studies of Government Use of Big Data in Latin America: Brazil and Mexico. 

Essentials

Künstliche Intelligenz hat sich vom Instrument zum Medium entwickelt. KI gestaltet die Wirtschaft, die Gesellschaft, bis hin zum Menschen selbst. Als Wissenschaft, die der Mathematik Flügel verleiht, ist KI höchst interessant. Besonders interessant sind Aufgaben, die KI heute erledigen kann. Das Interessanteste an dieser neuen Welt ist der Mensch, der KI versteht und intelligent nutzt. Das ist ein Mensch, der die Chancen, die KI ihm bietet, ergreift, ohne seine materielle und geistige Unabhängigkeit zu opfern. Als sechster Sinn – als Synthese von Mensch und Maschine – ist KI eine wunderbare Sache. Wir haben sie in der Hand! 
Das Essential ermöglicht, Fragen im Umgang mit der KI erörtern zu können, zum Beispiel: Was ist künstliche Intelligenz? Wohin führt die Paarung der Macht des Geldes mit der Autorität der künstlichen Intelligenz? Wer in kurzer Zeit den Mechanismus der KI von Grund auf verstehen, sie beurteilen und intelligent nutzen will, findet mit diesem Buch den richtigen Einstieg, illustriert durch kurze Beispiele aus Philosophie und Ethik, Wirtschaft und Politik, Umwelt und Natur, Informatik, Mathematik und Musik.

Der sechste Sinn und die Evolution der Informatik

KI verstehen und intelligent nutzen

Unlock the power of Oracle Database 23AI and Autonomous Database Serverless (ADB-S) with this comprehensive guide to the latest innovations in performance, security, automation, and AI-driven optimization. As enterprises embrace intelligent and autonomous data platforms, understanding these capabilities is essential for data architects, developers, and DBAs.

Explore cutting-edge features such as vector data types and AI-powered vector search, revolutionizing data retrieval in modern AI applications. Learn how schema privileges and the DB_DEVELOPER_ROLE simplify access control in multi-tenant environments. Dive into advanced auditing, SQL Firewall, and data integrity constraints to strengthen security and compliance.

Discover AI-driven advancements like machine learning-based query execution, customer retention prediction, and AI-powered query tuning. Additional chapters cover innovations in JSON, XML, JSON-Relational Duality Views, new indexing techniques, SQL property graphs, materialized views, partitioning, lock-free transactions, JavaScript stored procedures, blockchain tables, and automated bigfile tablespace shrinking.

What sets this book apart is its practical focus—each chapter includes real-world case studies and executable scripts, enabling professionals to implement these features effectively in enterprise environments. Whether you're optimizing performance or aligning IT with business goals, this guide is your key to building scalable, secure, and AI-powered solutions with Oracle 23AI and ADB-S.

What You Will Learn

Explore Oracle 23AI's latest features through real-world use cases

Implement AI/ML-driven optimizations for smarter, autonomous database performance

Gain hands-on experience with executable scripts and practical coding examples

Strengthen security and compliance using advanced auditing, SQL Firewall, and blockchain tables

Master high-performance techniques for query tuning, in-memory processing, and scalability

Revolutionize data access with AI-powered vector search in modern AI workloads

Simplify user access in multi-tenant environments using schema privileges and DB_DEVELOPER_ROLE

Model and query complex data using JSON-Relational Duality Views and SQL property graphs




Who this Book is For

Database architects, data engineers, Oracle developers, and IT professionals seeking to leverage Oracle 23AI’s latest features for real-world applications

Exploring New Features with Hands-On Case Studies

Oracle 23ai & ADBS in Action

Wer im Wettbewerb um Ausschreibungen überzeugen will, braucht mehr als gute Folien: Dieses Buch zeigt praxisnah, wie Sie mit professionell geführten, kundenorientierten Präsentationen Vertrauen schaffen und einen entscheidenden Unterschied machen. Kompakt formulierte Praxisanleitungen, innovative Methoden und konkrete Tipps helfen, auch anspruchsvolle Kunden wirkungsvoll vorzubereiten, nachhaltig zu begeistern und als Team zu glänzen.

Vertrauen aufbauen und perfekt präsentieren

Ausschreibungen gewinnen

Business Analytics in Practice

This book offers a comprehensive guide to blockchain analytics, from foundational concepts to advanced applications, crafted for professionals, academics, policymakers, and students. It begins with an introduction to blockchain technology and analytics, highlighting the unique structure of blockchain data, collection methods, and distinctions from traditional databases. Analytical techniques are covered in depth, including statistical and machine learning methods, real-time analysis, and predictive modeling.
It contains numerous practical industry use cases that demonstrate how blockchain analytics transforms finance, supply chain, and healthcare, enhancing fraud detection, data security, and product verification. Sections on security and privacy address tools to protect blockchain data and manage risks, while global regulatory insights emphasize transparency and policy development. It provides actionable insights on emerging integrations with AI, IoT, and quantum computing.
As such, industry leaders will discover frameworks for integrating blockchain into business, while academics gain insights into the analytic methodologies that underpin blockchain technology. Policymakers and government officials can use this resource to develop policies promoting transparency and security. For students and educators, the book serves as an essential foundation in blockchain, data analytics, and fintech.

Bridging Theory and Practice

Blockchain Analytics for Practitioners

Lecture Notes in Computer Science

This book LNCS 16213 constitutes the refereed proceedings of the 29th International Conference on Enterprise Design, Operations, and Computing, EDOC 2025, held in Lisbon, Portugal, during September 9–12, 2025.

The 19 full papers were carefully reviewed and seleced from 73 submissions. They were categorized under topical sections as follows:

1) Enterprise Architecture

2) Business Process Management

3) Business Processes &amp; Decision-Making

4) Modeling and Modeling Methods

5) Ontologies

6) Artificial Intelligence and Agents

29th International Conference, EDOC 2025, Lisbon, Portugal, September 9–12, 2025, Revised Selected Papers

Enterprise Design, Operations, and Computing

Focus on the code-first approach to developing a database with EFCore 10. Taking the code-first approach allows the entire database to be built and maintained in code so there is never a situation in which you cannot restore the database schema. Additionally, the code-first approach creates an entirely transparent record of changes to the database that is easily tracked in your source control. Emphasis throughout the book is on leaving you well positioned to architect and lead data development efforts for your organization.
New to This Edition
Demonstrate the Object Relational Mapper (ORM) of choice for working with databases for enterprise applications using .Net Framework from the ground up. This third edition is revised to cover modern EFCore development as of EFCore 10 and includes information and examples for changes from EFCore 7, 8, 9, and 10. Throughout the book, practical examples and considerations are presented to help you understand how to create robust and efficient database solutions.
What You Will Learn
¿&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Ability to build robust and maintainable database solutions using a code-first approach
¿&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; How to create and execute stored procedures, triggers, and functions
¿&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Skills, tips, and tricks to analyze and optimize performance of database queries
¿&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Confidence to architect data integrity through keys, constraints, and relationships
¿&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Understanding of Data Annotations and the Fluent API for enhancing solutions
¿&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Examples to leverage your learning, including information on the latest features in EFCore

Database Access for Enterprise Applications

Practical Entity Framework Core 10

Management for Professionals

This book offers a comprehensive guide for sports organizations to effectively manage and leverage data for optimal outcomes. It bridges theory and practice, providing frameworks for sports data strategy and analytics, and emphasizing data governance, quality, and security. Through case studies and examples, it demonstrates data-driven improvements in player recruitment, game strategy, fan engagement, and revenue generation. Exploring emerging trends like AI and machine learning, it empowers readers to make informed decisions and meet the growing demand for data-driven decision-making in sports. The book aims to unlock the potential of sports data for sustained success in the industry.

A Practical Guide for Sports Organizations

Data Excellence in Sports

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>
Who This Book is For
Product and data leads driving organizational transformation, product managers, team accountable leads, and data practitioners, such as data engineers, data analysts, data scientists, and ML engineers, who are willing to evolve their team's operating model to maximize value from data.

Strategies for Aligning Data and Product Teams to Transform Organizations

Data as a Product Driver

<div>
This book presents a practical and strategic roadmap for AI adoption through the lens of enterprise architecture. It tackles the urgent challenges organizations face, whether a startup, SMB, or large enterprise, when navigating the complexities of AI and Generative AI implementation on a global scale. Covering critical areas such as architectural readiness, governance, compliance, ethical considerations, integration hurdles, and scalability, the book provides actionable blueprints, decision frameworks, and real-world case studies to enable sustainable AI adoption. 
</div>
<div>
Structured around global trends, core enterprise layers (data, application, infrastructure, and business) and varying organizational maturity levels, it uniquely bridges the gap between high-level executive vision and on-the-ground architectural execution, while keeping the Human Endpoint Principle at its core—ensuring that every system ultimately serves people. 
</div>
<div>
¿You Will: 
</div>
<div>
<ul>
<li>
Learn how to assess your organization's readiness for AI and Generative AI adoption 




</li></ul></div>
<div>
<ul>
<li>

</li></ul></div>

From Vision to Scalable Execution

Architecting Enterprise AI Strategies

A new era of SQL Server is here, and this latest edition of Grant Fritchey’s best-selling dive into SQL Server query performance can ensure your queries keep up.

The fundamentals are still here: You’ll learn how statistics and indexes impact performance, how to identify poorly performing queries, and how to discover effective solutions. But this new edition also includes advanced features unique to SQL Server 2025, such as AI integration for automatic tuning, insights on using extended events, automatic execution plan correction, and more. It’s a must-have resource designed to empower you to troubleshoot slow-performing queries and make them run faster than ever.

The book is a treasure trove of instruction, insight, and advice. As you dive in, you’ll encounter key fundamentals, from statistics and data distribution to cardinality and parameter sniffing, and learn to analyze and design your indexes and queries using best practices that prevent performance problems before they occur. You’ll also explore advanced features like Query Store for managing and controlling execution plans, automated performance tuning, and memory-optimized OLTP tables and procedures—and learn how SQL Server 2025 makes it all more powerful and automatable than ever.

What You Will Learn

Use Query Store to understand and easily change query performance

Recognize and eliminate bottlenecks leading to slow performance

Tune queries whether on-premises, in containers, or on cloud platform providers

Implement best practices in T-SQL to minimize performance risk

Design in the performance that you need through careful query and index design

Understand how built-in, automatic tuning can assist your performance enhancement efforts

Protect query performance during upgrades to the newer versions of SQL Server




Who This Book Is For

Developers and database administrators with responsibility for query performance in SQL Server environments, and anyone responsible for writing or creating T-SQL queries and in need of insight into bottlenecks—including how to identify them, understand them, and eliminate them

Troubleshoot and Optimize Query Performance

SQL Server 2025 Query Performance Tuning

International Series in Operations Research & Management Science

This book presents a comprehensive examination of emerging digital innovations and their implications for supply chain management. Bridging theory and application, this book provides valuable insights into how technological advancements are influencing practice, policy, and research across global supply networks. The book begins with an overview of emerging technologies and their practical applications in supply chains. It then explores the use of blockchain to enhance traceability and observability, followed by a detailed look at data-driven analytics for building resilient and adaptive supply chains. The final section focuses on the transformative role of artificial intelligence in optimizing supply chain operations. 
This book can be used as an essential source for students and scholars who are interested in pursuing research or teaching courses on the rapidly evolving field of digital transformation in supply chains. It also provides valuable insights for managers and practitioners seeking to enhance their knowledge and effectively navigate the digital transformation of their supply chain operations.

Towards Digital Transformation

Emerging Technologies in Supply Chains

Contributions to Finance and Accounting

Chapter 1. Expertise in fund management (Fredrik Nilsson).- Chapter 2. Performance and fund managers’ expertise (Martin Abrahamson).- Chapter 3. Searching for expert fund managers (Martin Abrahamson).- Chapter 4. Judgments and decisions by expert fund managers (Martin Abrahamson).- Chapter 5. Individual foresight and fund management expertise (Melissa Innes).- Chapter 6. Artificial intelligence in discretionary fund management (Haojun Hu).- Chapter 7. Integrating ESG information in active fund management (Katarzyna Cieslak).- Chapter 8. Analysing fund managers’ accountability (Frank Hartmann).- Chapter 9. Does expertise matter? Concluding reflections (Fredrik Nilsson).

Exploring Fund Management Expertise

Big Data Applications and Use Cases

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