The book starts by introducing fundamental concepts of modern data architecture for AI, laying the groundwork for understanding its importance. It then digs deep into the aspects of data ingestion and collection strategies. Subsequently, it discusses data storage and management techniques that cater specifically to AI workloads. Readers will understand the concepts of data processing, transformation, and building scalable and efficient data pipelines, and how to orchestrate interconnected processes. The book further explores the topics of scalable ML infrastructure and stream processing, concluding with insights into visualization, explainable AI, and future trends.