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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

Questions

The following are additional questions from the Asking in the right direction section:

  • General questions: Your modern data warehouse may need to hold data for a longer period. Do you need different access tiers (hot, cool, or archive)? Is older data not accessed that often? How do you need to design the access rights to the data? Are there only automatic processes, or will users want to access data themselves? Do you need to establish replication for reliability, and to what extent?
  • Data loading: Are you planning for a new ETL/ELT tool? Do you want to run that in the cloud or on-premises? What are your expectations for the availability of connectors? What are your expectations for usability, or do you want to code your data transport layer? What language do you prefer for this? What will the volume of the data be that is to be transported? Do you need parallel processes? Do you expect scalability?
  • Data transformation: Do you want to perform data transformation...
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