Serverless ETL and Analytics with AWS Glue

<p><strong>Build efficient data lakes that can scale to virtually unlimited size using AWS Glue</strong></p><p><strong>Key Features:</strong></p><ol><li data-list=bullet><span class=ql-ui contenteditable=false></span>Learn to work with AWS Glue to overcome typical implementation challenges in data lakes</li><li data-list=bullet><span class=ql-ui contenteditable=false></span>Create and manage serverless ETL pipelines that can scale to manage big data</li><li data-list=bullet><span class=ql-ui contenteditable=false></span>Written by AWS Glue community members this practical guide shows you how to implement AWS Glue in no time</li></ol><p><strong>Book Description:</strong></p><p>Organizations these days have gravitated toward services such as AWS Glue that undertake undifferentiated heavy lifting and provide serverless Spark enabling you to create and manage data lakes in a serverless fashion. This guide shows you how AWS Glue can be used to solve real-world problems along with helping you learn about data processing data integration and building data lakes.</p><p>Beginning with AWS Glue basics this book teaches you how to perform various aspects of data analysis such as ad hoc queries data visualization and real-time analysis using this service. It also provides a walk-through of CI/CD for AWS Glue and how to shift left on quality using automated regression tests. You'll find out how data security aspects such as access control encryption auditing and networking are implemented as well as getting to grips with useful techniques such as picking the right file format compression partitioning and bucketing. As you advance you'll discover AWS Glue features such as crawlers Lake Formation governed tables lineage DataBrew Glue Studio and custom connectors. The concluding chapters help you to understand various performance tuning troubleshooting and monitoring options.</p><p>By the end of this AWS book you'll be able to create manage troubleshoot and deploy ETL pipelines using AWS Glue.</p><p><strong>What You Will Learn:</strong></p><ol><li data-list=bullet><span class=ql-ui contenteditable=false></span>Apply various AWS Glue features to manage and create data lakes</li><li data-list=bullet><span class=ql-ui contenteditable=false></span>Use Glue DataBrew and Glue Studio for data preparation</li><li data-list=bullet><span class=ql-ui contenteditable=false></span>Optimize data layout in cloud storage to accelerate analytics workloads</li><li data-list=bullet><span class=ql-ui contenteditable=false></span>Manage metadata including database table and schema definitions</li><li data-list=bullet><span class=ql-ui contenteditable=false></span>Secure your data during access control encryption auditing and networking</li><li data-list=bullet><span class=ql-ui contenteditable=false></span>Monitor AWS Glue jobs to detect delays and loss of data</li><li data-list=bullet><span class=ql-ui contenteditable=false></span>Integrate Spark ML and SageMaker with AWS Glue to create machine learning models</li></ol><p><strong>Who this book is for:</strong></p><p>This book is for ETL developers data engineers and data analysts who want to understand how AWS Glue can help you solve your business problems. Basic knowledge of AWS data services is assumed.</p>