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

Product type Paperback

Published in Jul 2021

Publisher Packt

ISBN-13 9781800562936

Length 520 pages

Edition 1st Edition

Tools

Azure

Concepts

Data Streaming

Author (1):

Patrik Borosch

View More author details

Table of Contents (20) Chapters

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

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Backing up and DR in Azure Synapse

There are several aspects that you need to consider when you are planning backup and DR in your Azure Synapse workspace. You'll need to take care of three main areas:

Data
Developed artifacts
Infrastructure setup

Backing up data

You will first look after your data and take care that you don't lose your biggest assets here. The two areas that you want to consider could be the following:

Storage accounts/data lakes
Dedicated SQL pools

As the serverless SQL pools and Spark pools are talking to the data lake, mainly you will cover those by backing up the data lake.

Backing up storage accounts/data lakes

A data lake/storage account can be prepared for DR in different ways. There are the following:

Automated redundancy built into the service. You have already learned about this in Chapter 3, Understanding the Data Lake Storage Layer. You can decide on the zone or geo-redundant storage...