04035nam a22005535i 4500 979-8-8688-0029-0 DE-He213 20251030110900.0 cr nn 008mamaa 231227s2024 xxu| s |||| 0|eng d 9798868800290 979-8-8688-0029-0 10.1007/979-8-8688-0029-0 doi QA76.585 UTC bicssc COM091000 bisacsh UTC thema Kumar, Anjani. author. aut http://id.loc.gov/vocabulary/relators/aut 68582 Architecting a Modern Data Warehouse for Large Enterprises [electronic resource] : Build Multi-cloud Modern Distributed Data Warehouses with Azure and AWS / by Anjani Kumar, Abhishek Mishra, Sanjeev Kumar. 1st ed. 2024. Berkeley, CA : Apress : Imprint: Apress, 2024. XV, 368 p. 146 illus. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda 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. Cloud Computing. 58386 Microsoft software. Microsoft .NET Framework. Computer networks . 60157 Cloud Computing. 58386 Microsoft. Computer Communication Networks. 65689 Mishra, Abhishek. author. aut http://id.loc.gov/vocabulary/relators/aut 68583 Kumar, Sanjeev. author. aut http://id.loc.gov/vocabulary/relators/aut 68584 SpringerLink (Online service) Springer Nature eBook Printed edition: 9798868800283 Printed edition: 9798868800306 Printed edition: 9798868805929 https://doi.org/10.1007/979-8-8688-0029-0 ZDB-2-CWD ZDB-2-SXPC 56910 56910