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Cloud Scale Analytics with Azure Data Services

Cloud Scale Analytics with Azure Data Services

By : Borosch
4.9 (7)
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Cloud Scale Analytics with Azure Data Services

Cloud Scale Analytics with Azure Data Services

4.9 (7)
By: Borosch

Overview of this book

Azure Data Lake, the modern data warehouse architecture, and related data services on Azure enable organizations to build their own customized analytical platform to fit any analytical requirements in terms of volume, speed, and quality. This book is your guide to learning all the features and capabilities of Azure data services for storing, processing, and analyzing data (structured, unstructured, and semi-structured) of any size. You will explore key techniques for ingesting and storing data and perform batch, streaming, and interactive analytics. The book also shows you how to overcome various challenges and complexities relating to productivity and scaling. Next, you will be able to develop and run massive data workloads to perform different actions. Using a cloud-based big data-modern data warehouse-analytics setup, you will also be able to build secure, scalable data estates for enterprises. Finally, you will not only learn how to develop a data warehouse but also understand how to create enterprise-grade security and auditing big data programs. By the end of this Azure book, you will have learned how to develop a powerful and efficient analytical platform to meet enterprise needs.
Table of Contents (20 chapters)
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1
Section 1: Data Warehousing and Considerations Regarding Cloud Computing
4
Section 2: The Storage Layer
7
Section 3: Cloud-Scale Data Integration and Data Transformation
14
Section 4: Data Presentation, Dashboarding, and Distribution

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...
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