Overview

Design Data Systems That Scale, Perform, and Deliver Unlock the skills to design scalable, reliable, and high-performance data systems that power analytics, AI, and real-time decision-making. System Design for Data Engineers is your complete guide to building modern data platforms using proven architectures, cloud-native tools, and industry best practices. Whether you're preparing for a data engineering interview, modernizing legacy pipelines, or launching enterprise-scale solutions, this book equips you with the patterns, techniques, and trade-offs every professional must master. What You'll Learn: ✅ Scalable data pipeline architecture (batch, streaming, hybrid) ✅ Real-time data processing with Flink, Spark, and Kafka ✅ Cloud vs. on-prem trade-offs for performance and cost ✅ High availability, fault tolerance, and disaster recovery strategies ✅ Data modeling essentials: OLTP, OLAP, star schema, partitioning ✅ Designing for consistency with CAP theorem and consensus protocols ✅ Security, privacy, and compliance for regulated industries Designed for working professionals, students, and teams, this book combines deep technical insights with real-world case studies-helping you not only understand system design but apply it effectively in production. If you want to create data systems that can handle massive scale, deliver results in milliseconds, and adapt to future demands, this book is your blueprint.

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