The Modern Data Warehouse in Azure: Building with Speed and Agility on Microsoft’s Cloud Platform - Softcover

How, Matt

Softcover

ISBN 10: 1484258223 ISBN 13: 9781484258224

Verlag: Apress, 2020

Inhaltsangabe

Build a modern data warehouse on Microsoft's Azure Platform that is flexible, adaptable, and fast―fast to snap together, reconfigure, and fast at delivering results to drive good decision making in your business.

Gone are the days when data warehousing projects were lumbering dinosaur-style projects that took forever, drained budgets, and produced business intelligence (BI) just in time to tell you what to do 10 years ago. This book will show you how to assemble a data warehouse solution like a jigsaw puzzle by connecting specific Azure technologies that address your own needs and bring value to your business. You will see how to implement a range of architectural patterns using batches, events, and streams for both data lake technology and SQL databases. You will discover how to manage metadata and automation to accelerate the development of your warehouse while establishing resilience at every level. And you will know how to feed downstream analytic solutions such as Power BI and Azure Analysis Services to empower data-driven decision making that drives your business forward toward a pattern of success.

This book teaches you how to employ the Azure platform in a strategy to dramatically improve implementation speed and flexibility of data warehousing systems. You will know how to make correct decisions in design, architecture, and infrastructure such as choosing which type of SQL engine (from at least three options) best meets the needs of your organization. You also will learn about ETL/ELT structure and the vast number of accelerators and patterns that can be used to aid implementation and ensure resilience. Data warehouse developers and architects will find this book a tremendous resource for moving their skills into the future through cloud-based implementations.

What You Will Learn

• Choose the appropriate Azure SQL engine for implementing a given data warehouse
  
• Develop smart, reusable ETL/ELT processes that are resilient and easily maintained
  
• Automate mundane development tasks through tools such as PowerShell
  
• Ensure consistency of data by creating and enforcing data contracts
  
• Explore streaming and event-driven architectures for data ingestion
• Create advanced staging layers using Azure Data Lake Gen 2 to feed your data warehouse
  

Who This Book Is For

Data warehouse or ETL/ELT developers who wish to implement a data warehouse project in the Azure cloud, and developers currently working in on-premise environments who want to move to the cloud, and for developers with Azure experience looking to tighten up their implementation and consolidate their knowledge

Über diesen Titel

Über die Autorin bzw. den Autor

Matt How is a professional consultant and international conference speaker who is passionate about data, analytics, and automation. Having spoken at several large conferences across the world, he is committed to sharing knowledge and insight with the wider community. Specializing in the design and delivery of modern data warehouse solutions using the Microsoft Azure Platform, Matt focuses on simplicity and resilience above all when designing cloud solutions. With a growing focus on data science, he is now researching techniques to integrate artificial intelligence capabilities into the modern data warehouse at scale.

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Build a modern data warehouse on Microsoft's Azure Platform that is flexible, adaptable, and fast―fast to snap together, reconfigure, and fast at delivering results to drive good decision making in your business.

Gone are the days when data warehousing projects were lumbering dinosaur-style projects that took forever, drained budgets, and produced business intelligence (BI) just in time to tell you what to do 10 years ago. This book will show you how to assemble a data warehouse solution like a jigsaw puzzle by connecting specific Azure technologies that address your own needs and bring value to your business. You will see how to implement a range of architectural patterns using batches, events, and streams for both data lake technology and SQL databases. You will discover how to manage metadata and automation to accelerate the development of your warehouse while establishing resilience at every level. And you will know how to feed downstream analytic solutions such as Power BI and Azure Analysis Services to empower data-driven decision making that drives your business forward toward a pattern of success.

This book teaches you how to employ the Azure platform in a strategy to dramatically improve implementation speed and flexibility of data warehousing systems. You will know how to make correct decisions in design, architecture, and infrastructure such as choosing which type of SQL engine (from at least three options) best meets the needs of your organization. You also will learn about ETL/ELT structure and the vast number of accelerators and patterns that can be used to aid implementation and ensure resilience. Data warehouse developers and architects will find this book a tremendous resource for moving their skills into the future through cloud-based implementations.

You will:

• Choose the appropriate Azure SQL engine for implementing a given data warehouse
  
• Develop smart, reusable ETL/ELT processes that are resilient and easily maintained
  
• Automate mundane development tasks through tools such as PowerShell
  
• Ensure consistency of data by creating and enforcing data contracts
  
• Explore streaming and event-driven architectures for data ingestion
• Create advanced staging layers using Azure Data Lake Gen 2 to feed your data warehouse
  

Details zur Ausgabe

• Verlag: Apress
• Erscheinungsdatum: 2020
• Sprache: Englisch
• ISBN 10: 1484258223
• ISBN 13: 9781484258224
• Einband: Taschenbuch
• Auflage: 1
• Anzahl der Seiten: 304
• Kontakt zum Hersteller: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Europaplatz 3; Heidelberg; 69115; Deutschland