Benner / Assoudi / Gulmammadov A Practical Guide to Oracle AI Engineering

Build intelligent apps with machine learning and AI across cloud and on-premises environments
1. Auflage 2026
ISBN: 978-1-80611-078-0
Verlag: Packt Publishing
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 354 Seiten

In A Practical Guide to Oracle AI Engineering, you'll learn how to tackle the challenges of building scalable, high-performance AI workflows in modern enterprises. Many organizations struggle to turn raw data into actionable insights while maintaining security, compliance, and operational efficiency. This book provides practical, end-to-end guidance for data engineers and architects to design, secure, implement, and optimize ML and GenAI solutions across Oracle Cloud, Oracle Database, and MySQL HeatWave.

Written by multiple Oracle experts with deep experience in Oracle technologies and enterprise data platforms, this book walks you through real-world examples and hands-on workflows, from data preparation and in-database ML to deploying GenAI-powered applications and intelligent agents. You'll gain skills in building pipelines, managing models, leveraging vector search for advanced AI use cases, and integrating AI into business applications with APEX and Oracle Digital Assistant. Advanced topics include scalable model deployment, serverless inference, monitoring, and MLOps best practices.

By the end, you'll be equipped to solve complex data challenges, accelerate AI adoption, and deliver measurable business impact through intelligent, production-ready solutions.

Autoren/Hrsg.

Benner, Erik

Assoudi, Hicham

Gulmammadov, Tural

Leseproben

Preface

Oracle has spent decades building one of the world’s most trusted enterprise technology platforms. From the early days of relational databases to today’s AI-driven cloud architecture, Oracle has continuously evolved to meet changing business demands. Now, with AI integrated directly into the database, embedded across cloud platform services, and enhanced through modern generative AI capabilities, Oracle is redefining enterprise AI.

This book explores that transformation.

For years, organizations treated AI as a separate ecosystem requiring specialized infrastructure, disconnected machine learning platforms, complex data pipelines, and costly integrations. Data had to be extracted from operational systems, copied into external platforms, transformed multiple times, and secured across various environments before meaningful intelligence could be generated. This often resulted in slow innovation, higher costs, fragmented governance, and unnecessary risks. Instead of forcing enterprises to move data to AI, Oracle brings AI directly to the data.

This architectural distinction is one of Oracle’s greatest competitive advantages and a central theme of this book. Oracle AI is not simply a collection of standalone machine learning services; it is a deeply integrated platform strategy spanning the Oracle Database, Oracle Cloud Infrastructure, platform as a service (PaaS) offerings, and enterprise-grade generative AI services.

Oracle Database 26ai and MySQL represent a major shift in enterprise data platforms. These databases are evolving from systems of record into systems of intelligence, with AI capabilities embedded directly where mission-critical business data resides. This reduces latency, lowers operational complexity, strengthens security, and accelerates enterprise AI adoption.

Beyond the database, Oracle Cloud Infrastructure extends this AI-first philosophy into the cloud. OCI was engineered for modern enterprise workloads, including large-scale AI and high-performance computing. Oracle’s networking architecture, bare metal performance, GPU infrastructure, RDMA cluster networking, and distributed cloud model provide the foundation for demanding AI training and inference workloads. Oracle also emphasizes predictable performance, cost efficiency, and enterprise interoperability.

Oracle’s generative AI services combine enterprise security, scalable infrastructure, and access to leading large language models through a unified cloud platform. Businesses can use these services for conversational AI, content generation, code assistance, document summarization, semantic search, intelligent agents, and industry-specific AI applications while maintaining enterprise-grade governance and data privacy.

Unlike many AI platforms focused on isolated use cases or demonstrations, Oracle integrates AI into real business operations across finance, healthcare, manufacturing, telecommunications, retail, government, and enterprise applications.

Throughout these chapters, we will explore:

• AI capabilities embedded directly inside Oracle Database
• Oracle Cloud Infrastructure for AI workloads
• Oracle AI and machine learning services
• Generative AI integration patterns
• Enterprise security and governance strategies
• Real-world business use cases and modernization scenarios
• AI-enabled application development
• Hybrid and distributed cloud AI architectures

The future belongs to integrated intelligence, where databases, applications, cloud infrastructure, and AI services operate as a unified platform.

Oracle is uniquely positioned to lead that future.

Who this book is for

This book is intended for architects, developers, database administrators, cloud engineers, IT leaders, and business decision makers who want to understand how Oracle AI technologies work together across the modern enterprise stack. Whether you are building AI-powered applications, modernizing legacy systems, implementing cloud-native architectures, or evaluating enterprise AI strategies, this book will provide both technical insight and business perspective.

What this book covers

, , introduces the Oracle AI ecosystem and provides an overview of Oracle Database, Oracle Cloud Infrastructure, Oracle AI Services, and Generative AI platforms. It also explains Oracle’s approach to in-database AI and enterprise AI architectures.

, , examines the AI and machine learning lifecycle using Oracle technologies, including enterprise AI design patterns, deployment strategies, and platform selection across Oracle Database, HeatWave, OCI AI Services, and Generative AI solutions.

, , explores data cleansing, transformation, feature engineering, and machine learning model training directly inside Oracle Database using Oracle Machine Learning capabilities.

, , focuses on deploying and managing machine learning models within Oracle environments, including model lifecycle management, scoring pipelines, REST interfaces, automation, version control, and monitoring techniques.

, , covers techniques for tuning AI and machine learning workloads using vector search optimization, parallel processing, indexing strategies, memory management, and autonomous database features.

, , introduces MySQL HeatWave and explains its role in AI and analytics architectures, including HeatWave architecture, setup, data loading, and foundational AI concepts.

, , explores deploying and optimizing machine learning models within MySQL HeatWave using HeatWave AutoML, in-database analytics, and query acceleration capabilities.

, , introduces Oracle Generative AI Services, large language models, retrieval-augmented generation, AI agents, and conversational AI architectures across OCI.

, , focuses on Oracle AI Services available through OCI, including prebuilt AI services for vision, language, speech, anomaly detection, forecasting, and document understanding.

, , explores the tools and workflows for building machine learning solutions using Oracle Data Science, including notebook environments, training pipelines, MLOps, and OCI integration.

, , explains how Oracle Digital Assistant enables organizations to build AI-powered chatbots, automate workflows, integrate backend systems, and deliver conversational experiences.

, , explores AI security, governance, compliance, responsible AI frameworks, and best practices for building scalable and trustworthy enterprise AI solutions using Oracle technologies.

To get the most out of this book

You will need a general understanding of the technologies outside of the AI use cases. You should understand the basics of Oracle Enterprise Edition, Oracle MySQL, and Oracle Cloud Infrastructure.

An understanding of Linux and python will be helpful for most of the examples. Most of the examples will need an OCI account. You can get a free OCI account from https://www.oracle.com/cloud/free/

Download the example code files

This book includes a complete downloadable code bundle containing all the example projects and files used throughout the chapters. We recommend downloading the bundle so you can follow along smoothly and experiment with the examples.

Use the bundle as a practical starting point. Modify it, extend it, and apply what you learn by creating your own variations as you progress through the chapters.

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