Architecting a Modern Data Warehouse for Large Enterprises (eBook, PDF) - Kumar, Anjani; Mishra, Abhishek; Kumar, Sanjeev
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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…mehr

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Produktbeschreibung
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 Learn

  • 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


Who This Book Is For

Experienced developers, cloud architects, and technology enthusiasts looking to build cloud-based modern data warehouses using Azure and AWS
Autorenporträt
Anjani Kumar is the Managing Director and Founder of MultiCloud4u, a rapidly growing startup that helps clients and partners seamlessly implement data-driven solutions for their digital businesses. With a background in computer science, Anjani began his career researching and developing multi-lingual systems that were powered by distributed processing and data synchronization across remote regions of India. He later collaborated with companies such as Mahindra Satyam, Microsoft, RBS, and Sapient to create data warehouses and other data-based systems that could handle high-volume data processing and transformation.

Abhishek Mishra is a Cloud Architect at a leading organization and has more than a decade and a half of experience building and architecting software solutions for large and complex enterprises across the globe. He has deep expertise in enabling digital transformations for his customers using the cloud and artificial intelligence.

Sanjeev Kumar heads up a global data and analytics practice at the leading and oldest multinational shoe company with headquarters in Switzerland. He has 19+ years of experience working for organizations modeling modern data solutions in multiple industries. He has consulted with some of the top multinational firms and enabled digital transformation for large enterprises using modern data warehouses in the cloud. He is an expert in multiple fields of modern data management and execution including data strategy, automation, data governance, architecture, metadata, modeling, business intelligence, data management, and analytics.