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Data Engineering with Apache Spark, Delta Lake, and Lakehouse

You're reading from   Data Engineering with Apache Spark, Delta Lake, and Lakehouse Create scalable pipelines that ingest, curate, and aggregate complex data in a timely and secure way

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Product type Paperback
Published in Oct 2021
Publisher Packt
ISBN-13 9781801077743
Length 480 pages
Edition 1st Edition
Languages
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Author (1):
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Manoj Kukreja Manoj Kukreja
Author Profile Icon Manoj Kukreja
Manoj Kukreja
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Table of Contents (17) Chapters Close

Preface 1. Section 1: Modern Data Engineering and Tools
2. Chapter 1: The Story of Data Engineering and Analytics FREE CHAPTER 3. Chapter 2: Discovering Storage and Compute Data Lakes 4. Chapter 3: Data Engineering on Microsoft Azure 5. Section 2: Data Pipelines and Stages of Data Engineering
6. Chapter 4: Understanding Data Pipelines 7. Chapter 5: Data Collection Stage – The Bronze Layer 8. Chapter 6: Understanding Delta Lake 9. Chapter 7: Data Curation Stage – The Silver Layer 10. Chapter 8: Data Aggregation Stage – The Gold Layer 11. Section 3: Data Engineering Challenges and Effective Deployment Strategies
12. Chapter 9: Deploying and Monitoring Pipelines in Production 13. Chapter 10: Solving Data Engineering Challenges 14. Chapter 11: Infrastructure Provisioning 15. Chapter 12: Continuous Integration and Deployment (CI/CD) of Data Pipelines 16. Other Books You May Enjoy

Section 3: Data Engineering Challenges and Effective Deployment Strategies

This part of the book educates you on the challenges faced by data engineering professionals. The concepts of Delta Lake are introduced. Lastly, a number of data engineering challenges will be highlighted with real-life examples of how Delta Lake can help deal with these issues effectively.

This section also educates you on effective deployment strategies for a data lake. Once the individual code components dealing with the various stages of data engineering have been built, these strategies play an important role in provisioning the cloud resources and deploying the data pipelines in a repeatable and continuous fashion.

This section contains the following chapters:

  • Chapter 9, Deploying and Monitoring Pipelines in Production
  • Chapter 10, Solving Data Engineering Challenges
  • Chapter 11, Infrastructure Provisioning
  • Chapter 12, Continuous Integration and Deployment (CI/CD) of Data Pipelines...
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