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Cloud Scale Analytics with Azure Data Services

You're reading from   Cloud Scale Analytics with Azure Data Services Build modern data warehouses on Microsoft Azure

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Product type Paperback
Published in Jul 2021
Publisher Packt
ISBN-13 9781800562936
Length 520 pages
Edition 1st Edition
Tools
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Author (1):
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Patrik Borosch Patrik Borosch
Author Profile Icon Patrik Borosch
Patrik Borosch
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Toc

Table of Contents (20) Chapters Close

Preface 1. Section 1: Data Warehousing and Considerations Regarding Cloud Computing
2. Chapter 1: Balancing the Benefits of Data Lakes Over Data Warehouses FREE CHAPTER 3. Chapter 2: Connecting Requirements and Technology 4. Section 2: The Storage Layer
5. Chapter 3: Understanding the Data Lake Storage Layer 6. Chapter 4: Understanding Synapse SQL Pools and SQL Options 7. Section 3: Cloud-Scale Data Integration and Data Transformation
8. Chapter 5: Integrating Data into Your Modern Data Warehouse 9. Chapter 6: Using Synapse Spark Pools 10. Chapter 7: Using Databricks Spark Clusters 11. Chapter 8: Streaming Data into Your MDWH 12. Chapter 9: Integrating Azure Cognitive Services and Machine Learning 13. Chapter 10: Loading the Presentation Layer 14. Section 4: Data Presentation, Dashboarding, and Distribution
15. Chapter 11: Developing and Maintaining the Presentation Layer 16. Chapter 12: Distributing Data 17. Chapter 13: Introducing Industry Data Models 18. Chapter 14: Establishing Data Governance 19. Other Books You May Enjoy

Chapter 2: Connecting Requirements and Technology

When you examine what cloud vendors are offering to form an analytical data estate, there is an abundance of options. Many data architects are investing a lot of time in carving out the right technology and the right tools to build on. This chapter will focus on the reference architecture of the modern data warehouse and introduce the suitable Microsoft Azure services with a short description, as well as the information you will need to select the right service to reach your goal.

In this chapter, we will cover the following topics:

  • Formulating your requirements
  • Understanding basic architecture patterns
  • Finding the right Azure tool for the right purpose
  • Understanding industry data models
  • Defining T-shirt sizes
  • Understanding the supporting services
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