AI Ready Data Blueprints

From Raw Data to AI-Driven Innovation

πŸ“…
May 2026
πŸ“Š
Intermediate
To Advanced
πŸ“š
200 Pages
⏱️
3h 13m
🌐
English
🏒
O'Reilly Media,
Inc.

Why This Book?

Transform your data infrastructure with proven patterns and expert guidance

🎯

Proven Patterns

Learn battle-tested data architecture patterns used by AWS customers worldwide

πŸ’‘

Real-World Examples

Practical implementations with working code samples you can use immediately

πŸš€

AI-Ready Architecture

Build data foundations that support modern AI and ML workloads

πŸ”§

AWS Best Practices

Learn directly from AWS experts with years of field experience

πŸ“Š

Data Governance

Implement robust data governance and compliance frameworks

⚑

Performance at Scale

Design systems that handle enterprise-scale data volumes efficiently

What You'll Learn

Comprehensive coverage of modern data architecture

1
Foundations of AI-Ready Data
Understanding data quality, governance, and architecture principles
2
Data Ingestion Patterns
Streaming and batch data ingestion architectures
3
Data Lake Architecture
Building scalable and secure data lakes on AWS
4
Data Transformation
ETL/ELT patterns and data processing frameworks
5
Machine Learning Data Pipelines
Feature engineering and ML data preparation
6
GenAI Data Requirements
Preparing data for generative AI applications

Get Your Copy

Available in print and digital formats from your favorite retailers

πŸ“– Format Options

πŸ“•
Print Edition

Traditional paperback format, perfect for your bookshelf

πŸ“±
Digital Edition

PDF, EPUB, and MOBI formats for all your devices

🎧
Audiobook

Listen and learn on the go (Amazon only)

Code Samples

Access working examples and implementation guides from the book

πŸ’»

Main Repository

Complete source code for all examples, organized by chapter. Includes infrastructure as code, sample datasets, and deployment scripts.

View on GitHub β†’
πŸ—οΈ

Data Lake Blueprints

Production-ready CloudFormation and Terraform templates for building modern data lakes with AWS services.

View on GitHub β†’
πŸ€–

ML Pipeline Examples

End-to-end machine learning pipelines with feature engineering, training, and deployment automation.

View on GitHub β†’
✨

GenAI Data Pipelines

Specialized data pipelines for generative AI, including vector databases and RAG implementations.

View on GitHub β†’

πŸš€ Getting Started

  1. Clone the repository to your local machine
  2. Review the README for prerequisites and setup instructions
  3. Follow chapter-specific guides in each directory
  4. Deploy examples to your AWS account

Download Blueprints

Free PDF blueprints and architecture diagrams to accelerate your projects

πŸ“

Data Lake Reference Architecture

Complete architecture diagram with component descriptions and best practices

2.3 MB β€’ 15 pages

πŸ”„

ETL Pipeline Patterns

Common data transformation patterns with implementation guidance

1.8 MB β€’ 12 pages

πŸ›‘οΈ

Data Governance Framework

Security, compliance, and governance best practices checklist

1.5 MB β€’ 10 pages

🎯

ML Feature Store Design

Architecture for scalable feature engineering and storage

2.1 MB β€’ 14 pages

⚑

Real-Time Data Streaming

Event-driven architecture patterns for streaming data

1.9 MB β€’ 11 pages

🧠

GenAI Data Architecture

Specialized patterns for generative AI and LLM applications

2.5 MB β€’ 16 pages

Request Engagement

Work with our team of experts for your data and AI initiatives

πŸ’Ό

Consulting Services

Get expert guidance on your data architecture and AI strategy

  • Architecture review and design
  • Data strategy development
  • Implementation roadmaps
  • Performance optimization
Request Consultation
🎀

Speaking Engagements

Book our authors for conferences, webinars, and corporate events

  • Keynote presentations
  • Technical deep dives
  • Panel discussions
  • Fireside chats
Book a Speaker
πŸŽ“

Training Workshops

Custom training programs for your teams and organizations

  • Hands-on workshops
  • Custom curriculum design
  • On-site or virtual delivery
  • Certification preparation
Schedule Training

Ready to Transform Your Data Strategy?

Contact us to discuss how we can help your organization build AI-ready data infrastructure

Get in Touch

πŸš€ 90 Days of Learning AI

Your daily journey to mastering AI - one infographic and video at a time

Your Learning Progress

0 of 90 days completed (0%)

Day 1
Day 1 - AI Acronyms Decoded
AI Acronyms Decoded

AI Acronyms Decoded: From LLMs to RAG and RLHF

Are you feeling overwhelmed by the "alphabet soup" of Artificial Intelligence? In today’s video, we break down the Definite Lexicon of AI Acronyms to help you navigate the rapidly evolving world of machine learning and data science.

Foundations Beginner
Day 2
Predictive vs Generative AI
Day 2 Infographic

Predictive vs Generative AI: What is the Difference

Are you confused about the different types of Artificial Intelligence? In this video, we explore the Dichotomy of Data, specifically the key differences between Predictive (Discriminative) AI and Generative AI.

Foundations Concepts
Day 3
LLM Architecture and Training Fundamentals
Day 3 Infographic

LLM Architecture and Training Fundamentals

A Large Language Model (LLM) is a Transformer-based neural network designed to generate human-like text by processing massive datasets and leveraging millions to billions of parameters. The development of these models follows a structured three-phase training process: pretraining for pattern recognition, fine-tuning for domain-specific adaptation, and instruction tuning or RLHF to ensure outputs align with human intent.

Machine Learning Algorithms
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