Performance Engineering for Data Systems

As data volumes grow, slow queries and inefficient pipelines cost organizations time and money. Understanding how to systematically analyze and resolve performance bottlenecks is a critical skill for any modern data professional. This course teaches you how to design, monitor, and optimize robust data systems for maximum efficiency. You will transition from writing basic queries to engineering high-performance data architectures. Through clear, written explanations and structured code analysis, you will learn the mechanics of query planners, execution engines, and storage formats. What you'll learn: - Understand core database storage engines, indexing strategies, and query execution plans - Optimize SQL queries by identifying and resolving common performance bottlenecks - Configure Spark jobs efficiently using modern memory management and partitioning techniques - Design data warehouse schemas optimized for analytical query performance - Apply modern data engineering practices including vectorization and columnar storage formats - Practice diagnosing system latency using profiling tools and execution metrics The course begins with foundational concepts of data storage and execution engines before progressing to advanced query tuning and Spark optimization strategies. You will study practical scenarios and analyze real-world performance patterns through comprehensive text-based walkthroughs. This course is designed for beginner to intermediate data engineers, database administrators, and data analysts who want to build faster, more scalable data systems. No advanced performance tuning experience is required, though a basic familiarity with SQL is recommended. Start optimizing your data systems today.