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You're reading from  Azure Data Engineer Associate Certification Guide

Product typeBook
Published inFeb 2022
PublisherPackt
ISBN-139781801816069
Edition1st Edition
Tools
Azure
Concepts
Big Data
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Author (1)
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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Summary

With that, we have come to the end of our third chapter. I hope you enjoyed learning about the different partitioning techniques available in Azure! We started with the basics of partitioning, where you learned about the benefits of partitioning; we then moved on to partitioning techniques for storage and analytical workloads. We explored the best practices to improve partitioning efficiency and performance. We understood the concept of distribution tables and how they impact the partitioning of Azure Synapse Analytics, and finally, we learned about storage limitations, which play an important role in deciding when to partition for ADLS Gen2. This covers the syllabus for the DP-203 exam, Designing a Partition Strategy. We will be reinforcing the learnings from this chapter via implementation details and tips in the following chapters.

Let's explore the serving layer in the next chapter.

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Azure Data Engineer Associate Certification Guide
Published in: Feb 2022Publisher: PacktISBN-13: 9781801816069
© 2022 Packt Publishing Limited All Rights Reserved

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

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