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Description of  Architecting a Modern Data Warehouse for Large Enterprises: Build Multi-cloud Modern Distributed Data Warehouses with Azure and AWS

B0CKQGGW8F pdf Design and architect new generation cloud-based data warehouses using Azure and AWS. This book provides an in-depth understanding of how to build modern cloud-native data warehouses, as well as their history and evolution.The book starts by covering foundational data warehouse concepts, and introduces modern features such as distributed processing, big data storage, data streaming, and processing data on the cloud. You will gain an understanding of the synergy, relevance, and usage data warehousing standard practices in the modern world of distributed data processing. The authors walk you through the essential concepts of Data Mesh, Data Lake, Lakehouse, and Delta Lake. And they demonstrate the services and offerings available on Azure and AWS that deal with data orchestration, data democratization, data governance, data security, and business intelligence. After completing this book, you will be ready to design and architect enterprise-grade, cloud-based modern data warehouses using industry best practices and guidelines.What You Will LearnUnderstand the core concepts underlying modern data warehousesUnderstand the core concepts underlying modern data warehousesDesign and build cloud-native data warehousesDesign and build cloud-native data warehousesGain a practical approach to architecting and building data warehouses on Azure and AWSImplement modern data warehousing components such as Data Mesh, Data Lake, Delta Lake, and LakehouseImplement modern data warehousing components such as Data Mesh, Data Lake, Delta Lake, and LakehouseProcess data through pandas and evaluate your model's performance using metrics such as F1-score, precision, and recallProcess data through pandas and evaluate your model's performance using metrics such as F1-score, precision, and recallApply deep learning to supervised, semi-supervised, and unsupervised anomaly detection tasks for tabular datasets and time series applicationsApply deep learning to supervised, semi-supervised, and unsupervised anomaly detection tasks for tabular datasets and time series applicationsWho This Book Is For Experienced developers, cloud architects, and technology enthusiasts looking to build cloud-based modern data warehouses using Azure and AWS