03705nam 2200577 450 991079925100332120240119114116.0979-88-6880-029-010.1007/979-8-8688-0029-0(CKB)29476471200041(DE-He213)979-8-8688-0029-0(MiAaPQ)EBC31051388(Au-PeEL)EBL31051388(OCoLC)1416369601(OCoLC-P)1416369601(CaSebORM)9798868800290(EXLCZ)992947647120004120240119d2024 uy 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierArchitecting a Modern Data Warehouse for Large Enterprises Build Multi-Cloud Modern Distributed Data Warehouses with Azure and AWS /Anjani Kumar, Abhishek Mishra, and Sanjeev KumarFirst edition.New York, NY :Apress Media LLC,[2024]©20241 online resource (XV, 368 p. 146 illus.) Includes index.9798868800283 Chapter 1: Introduction -- Chapter 2: Modern Data Warehouses -- Chapter 3: Data Lake, Lake House, and Delta Lake -- Chapter 4: Data Mesh -- Chapter 5: Data Orchestration Techniques -- Chapter 6: Data Democratization, Governance, and Security -- Chapter 7: Business Intelligence.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. You will: Understand the core concepts underlying modern data warehouses Design and build cloud-native data warehouses Gain a practical approach to architecting and building data warehouses on Azure and AWS Implement modern data warehousing components such as Data Mesh, Data Lake, Delta Lake, and Lakehouse Process data through pandas and evaluate your model’s performance using metrics such as F1-score, precision, and recall Apply deep learning to supervised, semi-supervised, and unsupervised anomaly detection tasks for tabular datasets and time series applications.Data warehousingMicrosoft Azure (Computing platform)Big dataBusiness enterprisesData processingData warehousing.Microsoft Azure (Computing platform)Big data.Business enterprisesData processing.005.7Kumar Anjani638545Mishra AbhishekKumar SanjeevMiAaPQMiAaPQMiAaPQBOOK9910799251003321Architecting a Modern Data Warehouse for Large Enterprises3871369UNINA