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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

Understanding CI/CD

The process of data transformation is continuous. In every modern organization, the volume and variety of data is increasing at a very high pace. As a result, the need for creating new or modifying existing data pipelines is very high. This sudden growth in data pipeline code is testing the limits of the traditional software delivery cycle.

As a result, organizations are eagerly looking forward to adopting viable methods that can accelerate product delivery, using a combination of best practices and automation. After all, streamlining the software cycle creates a clear path to success. Before we try to understand how CI/CD works, there is merit in understanding the traditional software delivery cycle.

Traditional software delivery cycle

Before we start talking about the modern approach to software delivery, let's understand how the traditional method has worked so far:

Figure 12.1 – Traditional software delivery cycle

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