دانلود کتاب راهنمای مطالعه دستیار مهندس داده دارای گواهینامه AWS

As Data Analytics Specialist Architects at Amazon Web Services (AWS), we—Sakti, Dylan, and Anusha—spent more than five years collaborating to solve some of the most challenging and innovative data problems for diverse clients. Our collective experience spans a wide range of industries and use cases: helping Chief Data Officers shape organizational data strategies, architecting petabyte-scale lakehouses, and building operationally excellent data platforms through proven best practices in performance, cost optimization, security, and comprehensive data governance. In today’s landscape, the demand for skilled data professionals has become more critical than ever, with the rise of generative AI compelling companies to leverage their data as a key business differentiator. Throughout our tenure at AWS, we were constantly asked by colleagues from diverse backgrounds how they could break into the dynamic field of data engineering. Our consistent recommendation was to use the AWS Certified Data Engineer Associate (DEA-C01) certification as a starting point. Our rationale is not simply about acquiring another credential but about leveraging the certification’s curriculum as a structured framework to gain a fundamental understanding of data engineering principles, both in general and specifically on the AWS Cloud. This book is the result of that shared experience and our passion for teaching, created to provide the clear, comprehensive, and practical guide we wished we had. Before we detail what this book covers, it’s important to clarify what it isn’t. This book is not an exhaustive deep dive into a single AWS service, nor is it a comprehensive manual for hands-on implementation. While many excellent books approach data engineering from a specific technology perspective, their focus can be narrow. Instead, our goal is to provide comprehensive coverage of the fundamental concepts and architectural patterns for data engineering on AWS.