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Professional and Applied Computing (R0)

Manpreet S. Brara

Subba Rao M.V. Parvathaneni

The SAP Fiori Handbook

A Step-By-Step Guide to SAP Fiori Essentials

&lt;p&gt;Chapter 1: Introduction to SAP Fiori.- Chapter 2: SAP Fiori Apps Reference Library.- Chapter 3: SAP Fiori Apps Recommendation Report.- Chapter 4: SAP Fiori Implementation and Deployment.- Chapter 5: SAP Fiori Configuration.- Chapter 6: Introduction to Fiori Apps.- Chapter 7: Introduction to SAP Fiori Catalogs.- Chapter 8: SAP Fiori Launchpad App Manager.- Chapter 9: SAP Fiori Launchpad Content Manager.- Chapter 10: Introduction to SAP Fiori Spaces and Pages.- Chapter 11: Converting SAP Fiori Groups to Pages.- Chapter 12: Configure Custom SAP Fiori Apps.- Chapter 13: SAP Fiori App Support and Troubleshooting.- Chapter 14: SAP Fiori Upgrade Impact Analysis.- Chapter 15: SAP Fiori Adapt UI.- Chapter 16: SAP Fiori Reports.&lt;/p&gt;

Adaptive Enterprise Architecture by Rubi Kaur is a practical guide for enterprise architects and technology leaders who need architecture to become a strategic, responsive capability rather than a static governance process.Drawing on decades of experience, this book explains why traditional enterprise architecture practices are no longer enough in a world shaped by AI, complex organizational structures, ESG requirements, technology supply chains and geopolitical risk. The book introduces the FLOW model, a practical approach to building architecture that evolves alongside changing business conditions.Through reflection prompts, practical experiments, practitioner interviews and real-world examples from financial services, telecommunications, the public sector and consulting, you will learn how to: - Build adaptive architecture that evolves with business priorities - Orchestrate across business, technology, people and AI - Create agile governance that responds to changing conditions - Reimagine the enterprise architect as a strategic orchestrator - Navigate complexity, emerging technology and interconnected business risksAdaptive Enterprise Architecture equips architects to operate in flow, strengthening strategic alignment, organizational adaptability and decision-making as technology and business conditions evolve.Themes include: enterprise architecture, adaptive architecture, AI strategy, agile governance, technology risk, business transformation

Shape the Flow of Value, Decisions and Innovation

Adaptive Enterprise Architecture

Chapter 1: Introduction to RHEL AI.- Chapter 2: Setting Up RHEL AI.- Chapter 3: Exploring Core Components.- Chapter 4: Advanced Features of RHEL AI.- Chapter 5: Developing Custom AI Applications.- Chapter 6: Monitoring and Maintenance.- Chapter 7: Use Cases and Best Practices.- Chapter 8: Future Trends in RHEL AI.- Chapter 9: Community and Support.

If you're looking to build, deploy, and scale AI solutions with confidence, 
 Practical RHEL AI
 is the guide you need. Whether you're an AI developer, data scientist, or DevOps engineer, this book walks you through the entire process—from setting up your AI development environment to optimizing and securing enterprise-scale AI workloads on Red Hat Enterprise Linux.
 You'll start with the essentials: installation, configuration, and leveraging powerful machine learning frameworks like TensorFlow, PyTorch, and Scikit-learn. Then, you’ll dive into the tools that make AI deployment seamless—GPU acceleration, containerization, and cloud integration with AWS and Azure.
 Security and compliance are non-negotiable in AI, and this book makes sure you get them right. Learn how to protect your models with encryption, implement role-based access control (RBAC), and meet industry standards like GDPR and HIPAA. You’ll also master AI workload monitoring with Prometheus and Grafana, troubleshoot common issues, and automate deployments with Ansible.&nbsp;However,&nbsp;theory only gets you so far—real-world applications make the difference. Through hands-on examples and case studies in healthcare, finance, and manufacturing, you’ll see how RHEL AI powers innovation in the field. Plus, you'll get insights into the future of AI, including Explainable AI (XAI), Edge AI, and AI governance. With 
 Practical RHEL AI,
 you’re not just learning AI—you’re building AI solutions that scale.
 You Will:<ul><li>Learn to Install and Configure RHEL AI to optimize machine learning workloads</li><li>Understand how to train and Deploy AI models using TensorFlow, PyTorch, and Scikit-learn</li><li>Explore how to Integrate and Implement GPU acceleration, cloud computing, and containerization for scalable AI solutions</li><li>Learn to Secure and Evaluate AI workloads with encryption, RBAC, and compliance best practices</li></ul>·&nbsp; &nbsp; &nbsp; This Book is for:AI and machine learning engineers, DevOps and system administrators, Data scientists, and IT professionals and cloud architects

Designing, Deploying and Scaling AI Solutions with Red Hat Enterprise Linux

Practical RHEL AI

<div>

Quickly find solutions to common problems when working with XML and JSON in SQL Server, now updated for SQL Server 2022 and 2025.

This second edition of XML and JSON Recipes for SQL Server expands the original with new recipes, including a dedicated section on FLWOR (For-Let-Where-Order By-Return) syntax for advanced XML querying. It also covers SQL Server's JSON data type introduced in SQL Server 2025 and the latest JSON functions added in SQL Server 2022, making it easier to build, query, and optimize structured data in modern SQL Server environments

A new chapter explores how XML and JSON are used in SQL Server system processes, including DDL triggers, Extended Events, execution plan parsing, and SSIS code-behind, helping you automate diagnostics and streamline development workflows. Whether you are building automation scripts, integrating with front-end applications, or managing cross-platform data exchange, this book provides practical, ready-to-use solutions.

Recipes are presented in a proven problem-solution format: look up the problem, read the solution, and apply it in your own code. Problem solved.
</div>
<div>
<div>What You Will Learn</div>
<div>

Build XML and JSON objects to support automation, integration, and data transfer.

Import and parse XML and JSON from operating system files and external sources.

Construct and optimize indexes on XML data to improve query performance.

Convert query result sets into JSON format and return them to tabular form.

Automate performance diagnostics by querying and parsing execution plans in XML.

Replace manual JSON workflows with SQL Server's built-in JSON functions.

Use FLWOR syntax for advanced XML filtering and transformation.

Work with the JSON data type introduced in SQL Server 2025.

Apply new JSON functions added in SQL Server 2022 for efficient data handling.

Parse and analyze Extended Events, SSIS code-behind, and DDL triggers using XML and JSON.

Leverage XML and JSON in SQL Server system processes for automation and monitoring.



</div>
<div>Who This Book Is For</div>
<div>Database administrators, .NET developers, business intelligence developers, and other data professionals who need a deep, practical skill set for working with XML and JSON in SQL Server. Also useful for web developers who need to transform database result sets into JSON for front-end applications and for teams managing automation, integration, and cross-platform data exchange.</div>

</div>

Quickly find solutions to common problems when working with XML and JSON in SQL Server, now updated for SQL Server 2022 and 2025.This second edition of XML and JSON Recipes for SQL Server expands the original with new recipes, including a dedicated section on FLWOR (For-Let-Where-Order By-Return) syntax for advanced XML querying. It also covers SQL Server's JSON data type introduced in SQL Server 2025 and the latest JSON functions added in SQL Server 2022, making it easier to build, query, and optimize structured data in modern SQL Server environmentsA new chapter explores how XML and JSON are used in SQL Server system processes, including DDL triggers, Extended Events, execution plan parsing, and SSIS code-behind, helping you automate diagnostics and streamline development workflows. Whether you are building automation scripts, integrating with front-end applications, or managing cross-platform data exchange, this book provides practical, ready-to-use solutions.Recipes are presented in a proven problem-solution format: look up the problem, read the solution, and apply it in your own code. Problem solved.What You Will Learn<ul><li>Build XML and JSON objects to support automation, integration, and data transfer.</li><li>Import and parse XML and JSON from operating system files and external sources.</li><li>Construct and optimize indexes on XML data to improve query performance.</li><li>Convert query result sets into JSON format and return them to tabular form.</li><li>Automate performance diagnostics by querying and parsing execution plans in XML.</li><li>Replace manual JSON workflows with SQL Server's built-in JSON functions.</li><li>Use FLWOR syntax for advanced XML filtering and transformation.</li><li>Work with the JSON data type introduced in SQL Server 2025.</li><li>Apply new JSON functions added in SQL Server 2022 for efficient data handling.</li><li>Parse and analyze Extended Events, SSIS code-behind, and DDL triggers using XML and JSON.</li><li>Leverage XML and JSON in SQL Server system processes for automation and monitoring.</li></ul>Who This Book Is For
 Database administrators, .NET developers, business intelligence developers, and other data professionals who need a deep, practical skill set for working with XML and JSON in SQL Server. Also useful for web developers who need to transform database result sets into JSON for front-end applications and for teams managing automation, integration, and cross-platform data exchange.

A Problem-Solution Approach

XML and JSON Recipes for SQL Server

The Modern Enterprise Architect: A New Era, A New Purpose, A New Approach reframes enterprise architecture as a strategic leadership discipline that connects vision to execution. Rather than treating architecture as a narrow technical function, Paul Gadbois presents a practical model for translating strategic goals into objectives, critical success factors, business capabilities, and enabling technology. This book equips leaders, architects, and transformation teams with a structured approach for aligning business strategy, delivery, and technology investment so organizations can efficiently move from ideas to measurable value.

A New Era, a New Purpose, a New Approach

THE MODERN ENTERPRISE ARCHITECT

An End-to-End Guide to Building Production-Ready AI Systems

GenAI Enterprise Implementation Blueprint

<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>

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.&nbsp;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.&nbsp; You Will:&nbsp;<ul><li>Learn how to assess your organization's readiness for AI and Generative AI adoption&nbsp;</li></ul><ul><li>Discover frameworks that align AI with business goals, governance, and compliance while confronting ethical risks.</li><li>Understand why many AI projects fail to deliver expected value and how to avoid adoption turning into loss.</li><li>Apply enterprise architecture strategies to embed AI across data, applications, and infrastructure with built-in governance, scalability, and human-centered sustainability.&nbsp;</li></ul> This book is for: Enterprise Architects, CTOs, as well as students and professionals eager to explore how AI can be adopted responsibly and sustainably across organizations of every scale.&nbsp;

From Vision to Scalable Execution

Architecting Enterprise AI Strategies

Sie arbeiten zum ersten Mal mit der SAP-Software oder sind als Umsteiger von SAP ERP plötzlich mit SAP S/4HANA konfrontiert? Dann ist dieser Schnelleinstieg mit seinem kompakten Überblick über den Funktionsumfang und einer anschaulichen Einführung in die Benutzeroberfläche SAP Fiori für Sie genau richtig.Was sich hinter den Begriffen ERP, HANA und S/4HANA verbirgt, wird ebenso skizziert wie die drei Lizenzmodelle von S/4HANA, On-Premise sowie Public und Private Cloud. Da ein Cloud-Deployment die Präferenz der SAP und inzwischen ausschließliche Option für Neukunden ist, wurde in der vorliegenden Neuauflage darauf ein besonderes Augenmerk gelegt.Sie lernen die wesentlichen integrierten Geschäftsprozesse kennen und deren Abbildung in SAP S/4HANA mithilfe von Fiori-Apps. Dazu nehmen die Autoren Sie mit in die Module rund um die Logistik wie Materialwirtschaft, Vertrieb und Versand sowie Produktionsplanung und -steuerung, um anschließend die Integration in die Finanzbuchhaltung und das Controlling aufzuzeigen. Sie präsentieren jeweils die wichtigsten Funktionen sowie Organisations- und Stammdatenobjekten und vermitteln, welche Komponenten welchen Modulen zuzuordnen sind.Fallbeispiele illustrieren schließlich den integrativen Ablauf der drei wichtigsten End-to-End-Prozesse in SAP S/4HANA: Order to Cash, Purchase to Pay und Forecast to Fulfill.<ul><li>Modulübergreifende Darstellung der zentralen Geschäftsprozesse</li><li>SAP-Grundbegriffe einfach und verständlich erklärt</li><li>Die Benutzeroberfläche SAP Fiori</li><li>Inklusive 7 Stunden Videomaterial</li>
 </ul>

Schnelleinstieg in SAP S/4HANA

This book equips AI developers, machine learning engineers, and software architects with the knowledge and tools needed to design, build, and deploy scalable autonomous agents. Beginning with foundational concepts in LLMs and agent architectures, the book transitions into hands-on design patterns and real-world implementation guidance. Readers will follow practical Python examples using cutting-edge frameworks like LangChain and AutoGen, with full reproducible code available on GitHub.
Emphasizing engineering essentials scalability, interoperability, observability, and ethics the book dives into multi-agent coordination, including emerging protocols such as MCP and A2A. It wraps up with compelling case studies from customer service bots to multi-agent analytics systems demonstrating how to build secure, stable, and trust-aligned AI agents. This guide bridges theory with practice for the modern AI practitioner.
You Will:
<ul>
<li>Discover reusable patterns such as reactors, planners, and tool-using agents that power effective autonomous systems.</li>
<li>Learn to build agents using Python with popular frameworks like LangChain and AutoGen, complete with reproducible GitHub code.</li>
<li>Dive into cutting-edge coordination mechanisms (e.g., MCP, A2A) that enable agents to collaborate and assign tasks dynamically.</li>
</ul>
&nbsp;
This book is for : Software Architects &amp; System Designers
&nbsp;

This book equips AI developers, machine learning engineers, and software architects with the knowledge and tools needed to design, build, and deploy scalable autonomous agents. Beginning with foundational concepts in LLMs and agent architectures, the book transitions into hands-on design patterns and real-world implementation guidance. Readers will follow practical Python examples using cutting-edge frameworks like LangChain and AutoGen, with full reproducible code available on GitHub.Emphasizing engineering essentials scalability, interoperability, observability, and ethics the book dives into multi-agent coordination, including emerging protocols such as MCP and A2A. It wraps up with compelling case studies from customer service bots to multi-agent analytics systems demonstrating how to build secure, stable, and trust-aligned AI agents. This guide bridges theory with practice for the modern AI practitioner.You Will:<ul><li>Discover reusable patterns such as reactors, planners, and tool-using agents that power effective autonomous systems.</li><li>Learn to build agents using Python with popular frameworks like LangChain and AutoGen, complete with reproducible GitHub code.</li><li>Dive into cutting-edge coordination mechanisms (e.g., MCP, A2A) that enable agents to collaborate and assign tasks dynamically.</li></ul>&nbsp;This book is for : Software Architects &amp; System Designers&nbsp;

Architecting Scalable, Ethical, and Trustworthy Systems for Enterprise

Agentic AI Systems in Practice

Design, build, and operate a production-grade analytics platform on Snowflake. This practical guide shows how Snowflake architecture shapes modeling, ingestion, and transformation choices; how to engineer ELT pipelines for structured and semi-structured data; and how to make performance, workload, security, and cost decisions that stand up in real projects. The approach is engineering-first and scenario-driven, turning concepts into repeatable, auditable solutions teams can use day to day.

Beyond feature coverage, the emphasis is operations: CI/CD for SQL and Snowpark code, monitoring and observability, least-privilege governance with roles and policies, cost guardrails, secure sharing and collaboration, and business continuity with Time Travel, cloning, and replication. You will learn Snowflake-specific techniques for pruning, selective clustering, streaming and CDC, and dynamic refresh.

What makes this book especially useful is its end-to-end operating playbook: opinionated patterns, checklists, and guardrails that connect architecture, modeling, ingestion and ELT, governance and security, performance and cost, and the everyday practices of releasing and recovering safely. It focuses on concrete decisions and the trade-offs behind them, helping teams avoid legacy anti-patterns while building a reliable, auditable platform that is ready to evolve.

What You Will Learn

Design Snowflake architectures that align storage, compute, security, and governance into a coherent, scalable platform.

Model, load, and transform structured and semi-structured data using streams, tasks, MERGE, and SCD2 patterns.

Tune performance and control cost with micro-partition pruning, selective clustering, warehouse sizing, and workload isolation.

Implement least-privilege RBAC, masking and row access policies, auditing, and tag-driven governance.

Build reliable ELT pipelines and release safely with CI/CD, testing, cloning, and SWAP-based promotion.

Operate with observability and SRE practices using Snowflake usage views and SLOs.

Share and collaborate securely with Secure Data Sharing and Marketplace, and plan replication and DR for continuity.




Who This Book Is For

Data engineers; data warehouse and solution architects; analytics engineers; BI developers; advanced data analysts; DBAs moving from on-prem to cloud (intermediate level with SQL and warehousing basics).

Design, build, and operate a production-grade analytics platform on Snowflake. This practical guide shows how Snowflake architecture shapes modeling, ingestion, and transformation choices; how to engineer ELT pipelines for structured and semi-structured data; and how to make performance, workload, security, and cost decisions that stand up in real projects. The approach is engineering-first and scenario-driven, turning concepts into repeatable, auditable solutions teams can use day to day.Beyond feature coverage, the emphasis is operations: CI/CD for SQL and Snowpark code, monitoring and observability, least-privilege governance with roles and policies, cost guardrails, secure sharing and collaboration, and business continuity with Time Travel, cloning, and replication. You will learn Snowflake-specific techniques for pruning, selective clustering, streaming and CDC, and dynamic refresh.What makes this book especially useful is its end-to-end operating playbook: opinionated patterns, checklists, and guardrails that connect architecture, modeling, ingestion and ELT, governance and security, performance and cost, and the everyday practices of releasing and recovering safely. It focuses on concrete decisions and the trade-offs behind them, helping teams avoid legacy anti-patterns while building a reliable, auditable platform that is ready to evolve.What You Will Learn<ul><li>Design Snowflake architectures that align storage, compute, security, and governance into a coherent, scalable platform.</li><li>Model, load, and transform structured and semi-structured data using streams, tasks, MERGE, and SCD2 patterns.</li><li>Tune performance and control cost with micro-partition pruning, selective clustering, warehouse sizing, and workload isolation.</li><li>Implement least-privilege RBAC, masking and row access policies, auditing, and tag-driven governance.</li><li>Build reliable ELT pipelines and release safely with CI/CD, testing, cloning, and SWAP-based promotion.</li><li>Operate with observability and SRE practices using Snowflake usage views and SLOs.</li><li>Share and collaborate securely with Secure Data Sharing and Marketplace, and plan replication and DR for continuity.</li></ul>Who This Book Is ForData engineers; data warehouse and solution architects; analytics engineers; BI developers; advanced data analysts; DBAs moving from on-prem to cloud (intermediate level with SQL and warehousing basics).&nbsp;

Architecture, Modeling, ELT Pipelines, and Operations

Snowflake Data Warehouse Engineering

Certification Study Companion Series

This book is the ultimate study companion for Red Hat's RHCSA certification, aligning with the release of Red Hat Enterprise Linux (RHEL) 10 in 2025.

As the foundational certification for Enterprise Linux administrators, the RHCSA exam validates essential system administration skills. This book is designed to sit along aside official documentation and study guides and covers all exam topics. Its primary objective is to help readers pass the practical exam by emphasizing real-world system administration tasks through a hands-on, task-based approach. Additionally, all examples and lab exercises will be accessible via GitHub for further practice.

The book is structured into twelve chapters, each addressing critical exam objectives, including system operations, networking, security, storage, and automation. Early chapters introduce fundamental Linux tools, shell scripting, and system management, while later sections cover advanced topics such as user and group administration, SELinux security, and container management. Each chapter contains practical exercises and review questions to reinforce learning. Key topics include configuring local and network storage, managing file permissions, scheduling tasks, securing SSH authentication, and deploying services within containers.

With a focus on practical skills, the book ensures readers gain hands-on experience with tasks such as system boot troubleshooting, process management, and configuring network firewalls. The annex provides answers to all review questions, offering a valuable self-assessment resource. Whether you are new to Linux administration or seeking certification to advance your career, this book serves as a comprehensive and structured study guide to mastering RHCSA 10.

What You'll Learn:

Master the process of RHEL installation, partitioning, and network configuration.

Study logical volume management (LVM), disk partitioning, and mounting file systems, ensuring you can handle storage challenges with confidence.

Learn Firewall configuration with firewalld, SELinux management, and basic security hardening techniques are crucial in today's threat landscape




This Book is for:

Individuals new to the field of Linux system administration.

IT Professionals Seeking to Enhance Linux Skills.

Developers and DevOps Engineers since a solid understanding of Linux system administration is crucial in modern development and DevOps environments.

This book is the ultimate study companion for Red Hat's RHCSA certification, aligning with the release of Red Hat Enterprise Linux (RHEL) 10 in 2025.As the foundational certification for Enterprise Linux administrators,&nbsp; the RHCSA exam validates essential system administration skills. This book is designed to sit along aside official documentation and study guides and covers all exam topics. Its primary objective is to help readers pass the practical exam by emphasizing real-world system administration tasks through a hands-on, task-based approach. Additionally, all examples and lab exercises will be accessible via GitHub for further practice.The book is structured into twelve chapters, each addressing critical exam objectives, including system operations, networking, security, storage, and automation. Early chapters introduce fundamental Linux tools, shell scripting, and system management, while later sections cover advanced topics such as user and group administration, SELinux security, and container management. Each chapter contains practical exercises and review questions to reinforce learning. Key topics include configuring local and network storage, managing file permissions, scheduling tasks, securing SSH authentication, and deploying services within containers.With a focus on practical skills, the book ensures readers gain hands-on experience with tasks such as system boot troubleshooting, process management, and configuring network firewalls. The annex provides answers to all review questions, offering a valuable self-assessment resource. Whether you are new to Linux administration or seeking certification to advance your career, this book serves as a comprehensive and structured study guide to mastering RHCSA 10.What You'll Learn:<ul><li>Master the process of RHEL installation, partitioning, and network configuration.</li><li>Study logical volume management (LVM), disk partitioning, and mounting file systems, ensuring you can handle storage challenges with confidence.</li><li>Learn&nbsp;Firewall configuration with firewalld, SELinux management, and basic security hardening techniques are crucial in today's threat landscape</li></ul>This Book is for:<ul><li>Individuals new to the field of Linux system administration.</li><li>IT Professionals Seeking to Enhance Linux Skills.</li><li>Developers and DevOps Engineers since a solid understanding of Linux system administration is crucial in modern development and DevOps environments.</li></ul>

Getting Ready for the EX200 Exam

Red Hat RHCSA 10 Study Companion

The SAP Fiori Handbook

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