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You're reading from  Azure Data Engineer Associate Certification Guide

Product typeBook
Published inFeb 2022
PublisherPackt
ISBN-139781801816069
Edition1st Edition
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Newton Alex
Newton Alex
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Newton Alex

Newton Alex leads several Azure Data Analytics teams in Microsoft, India. His team contributes to technologies including Azure Synapse, Azure Databricks, Azure HDInsight, and many open source technologies, including Apache YARN, Apache Spark, and Apache Hive. He started using Hadoop while at Yahoo, USA, where he helped build the first batch processing pipelines for Yahoo's ad serving team. After Yahoo, he became the leader of the big data team at Pivotal Inc., USA, where he was responsible for the entire open source stack of Pivotal Inc. He later moved to Microsoft and started the Azure Data team in India. He has worked with several Fortune 500 companies to help build their data systems on Azure.
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Implementing data redundancy

Data redundancy is the process of storing multiple copies of data at different locations, in order to protect the data from events such as power failures, disk failures, network failures, and even major catastrophes such as entire data center outages. Azure Storage provides multiple options for data redundancy both at local data center levels and across data centers. We can broadly group the options into these two categories:

  • Primary region redundancy
  • Secondary region redundancy

Let's look at these options in detail.

Azure storage redundancy in the primary region

This type of redundancy covers localized failures such as disk failures, machine failures, and rack failures. There are two types of primary region redundancy, as detailed next.

Locally redundant storage (LRS)

With this type of redundancy, the data is copied three times across multiple machines in the same physical region within a data center. This option provides...

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Azure Data Engineer Associate Certification Guide
Published in: Feb 2022Publisher: PacktISBN-13: 9781801816069

Author (1)

author image
Newton Alex

Newton Alex leads several Azure Data Analytics teams in Microsoft, India. His team contributes to technologies including Azure Synapse, Azure Databricks, Azure HDInsight, and many open source technologies, including Apache YARN, Apache Spark, and Apache Hive. He started using Hadoop while at Yahoo, USA, where he helped build the first batch processing pipelines for Yahoo's ad serving team. After Yahoo, he became the leader of the big data team at Pivotal Inc., USA, where he was responsible for the entire open source stack of Pivotal Inc. He later moved to Microsoft and started the Azure Data team in India. He has worked with several Fortune 500 companies to help build their data systems on Azure.
Read more about Newton Alex