AI-Driven Data Engineering Tools, Techniques, and Best Practices for Next-Gen Data Pipelines

This book dives deep into how AI and machine learning are revolutionizing traditional data workflows-automating ETL processes, optimizing data quality, improving scalability, and enabling real-time analytics at scale. With practical insights and hands-on examples, readers will learn how to design intelligent data pipelines, leverage AI for anomaly detection and schema evolution, and integrate advanced tools like Apache Spark, Airflow, and cloud-native platforms.
Perfect for data engineers, architects, and tech-savvy professionals, this book provides a future-forward approach to data engineering that's efficient, adaptive, and ready for the demands of AI-powered ecosystems. Whether you're building data infrastructure from scratch or modernizing legacy systems, this guide will help you engineer data with intelligence at its core.