Data Engineering on AWS Vol 1 - OLAP & Data Warehouse

Master AWS Redshift for data warehousing, including infrastructure setup, advanced database objects, performance tuning, workload management, and robust security controls. Gain practical skills to optimize and secure large-scale analytics environments. This course provides a comprehensive exploration of AWS Redshift, from infrastructure and architecture to deep dives into database objects, ACID compliance, and advanced features. Learners will develop expertise in query tuning, workload management, and implementing security measures such as RBAC, row and column-level security, and dynamic data masking. The course also covers monitoring, serverless options, pricing, integration with AWS services, and best practices for Redshift administration. Through detailed explanations and guided walkthroughs, learners build practical knowledge of Redshift's capabilities, focusing on performance optimization, security, and operational excellence. The course emphasizes hands-on understanding of Redshift features and their application in real-world data warehouse scenarios. This course is part two of a three-course Specialization designed to build a complete and cohesive understanding of the subject. While it offers valuable skills on its own, you'll gain the most benefit by progressing through all three courses as a structured learning journey. This course is based on Data Engineering on AWS Vol 1 - OLAP & Data Warehouse, by Soumyadeep Dey. This course is licensed and distributed by Packt. All rights reserved. Packt is one of the world's most prolific publishers of cutting-edge technical content. For over two decades we've made it our mission to curate and publish the knowledge of only the very best technical experts. We focus on real-world courses that help our customers get the job done, with coverage that extends across a wide range of established and cutting-edge technical topics. If you're an individual or an organisation that embraces learning by doing, Packt is the perfect fit for you.

Build a strong foundation in data engineering concepts and AWS distributed storage, focusing on S3 and essential data modeling techniques. Learn how to design, secure, and optimize storage solutions for analytics and reporting. This course introduces the core principles of data engineering, including OLTP, OLAP, data marts, data lakes, and data lakehouse architectures. Learners will explore AWS S3 in depth, covering storage classes, security, performance, and architectural patterns. The course also covers data modeling fundamentals such as normalization, ER diagrams, and dimensional modeling, preparing learners to structure data effectively for analytics workloads. Learners progress through a blend of conceptual explanations and practical demonstrations, focusing on real-world scenarios and AWS best practices. The course emphasizes understanding foundational concepts and applying them to design robust, secure, and scalable storage and modeling solutions. This course is part one of a three-course Specialization designed to build a complete and cohesive understanding of the subject. While it offers valuable skills on its own, you'll gain the most benefit by progressing through all three courses as a structured learning journey. This course is based on Data Engineering on AWS Vol 1 - OLAP & Data Warehouse, by Soumyadeep Dey. This course is licensed and distributed by Packt. All rights reserved. Packt is one of the world's most prolific publishers of cutting-edge technical content. For over two decades we've made it our mission to curate and publish the knowledge of only the very best technical experts. We focus on real-world courses that help our customers get the job done, with coverage that extends across a wide range of established and cutting-edge technical topics. If you're an individual or an organisation that embraces learning by doing, Packt is the perfect fit for you.