This Specialization equips data engineers and database professionals with comprehensive skills to optimize performance across SQL databases, data warehouses, and Apache Spark environments. Through eleven hands-on courses, learners progress from SQL query optimization and schema design to advanced topics including cloud infrastructure engineering, disaster recovery architecture, and distributed system tuning. You will analyze execution plans, implement strategic partitioning and caching, design cost-effective multi-cluster architectures, and apply Infrastructure as Code for resilient data platforms. By completion, you will possess the technical expertise to diagnose performance bottlenecks, optimize resource allocation, and build scalable data systems that deliver measurable business value while maintaining security and reliability standards.
Applied Learning Project
Throughout this Specialization, learners complete authentic performance engineering projects that mirror real-world enterprise challenges. You will analyze SQL execution plans to diagnose and resolve query bottlenecks, design optimized database schemas using partitioning and clustering strategies, and implement Infrastructure as Code to provision resilient cloud data warehouses. Projects include conducting cost-versus-performance benchmarking for storage architecture decisions, building automated SCD pipelines for historical data management, and optimizing Spark job execution through systematic analysis of shuffle operations and data skew. Each project requires applying analytical skills to authentic datasets, enabling you to demonstrate measurable performance improvements and justify architectural decisions with data-driven recommendations.
