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Modern Data Architectures with Python

You're reading from   Modern Data Architectures with Python A practical guide to building and deploying data pipelines, data warehouses, and data lakes with Python

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Product type Paperback
Published in Sep 2023
Publisher Packt
ISBN-13 9781801070492
Length 318 pages
Edition 1st Edition
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Author (1):
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Brian Lipp Brian Lipp
Author Profile Icon Brian Lipp
Brian Lipp
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Toc

Table of Contents (19) Chapters Close

Preface 1. Part 1:Fundamental Data Knowledge
2. Chapter 1: Modern Data Processing Architecture FREE CHAPTER 3. Chapter 2: Understanding Data Analytics 4. Part 2: Data Engineering Toolset
5. Chapter 3: Apache Spark Deep Dive 6. Chapter 4: Batch and Stream Data Processing Using PySpark 7. Chapter 5: Streaming Data with Kafka 8. Part 3:Modernizing the Data Platform
9. Chapter 6: MLOps 10. Chapter 7: Data and Information Visualization 11. Chapter 8: Integrating Continous Integration into Your Workflow 12. Chapter 9: Orchestrating Your Data Workflows 13. Part 4:Hands-on Project
14. Chapter 10: Data Governance 15. Chapter 11: Building out the Groundwork 16. Chapter 12: Completing Our Project 17. Index 18. Other Books You May Enjoy

Orchestrating Your Data Workflows

We have covered a wealth of techniques and knowledge in building our data platforms. However, there are some missing components in fully orchestrating everything. We’ve mentioned Databricks Workflows, but we didn’t dive deep into how it works; we also haven’t mentioned logging or secrets management. Workflows is an orchestration tool that’s used to manage data pipelines in Databricks. Orchestration tools normally allow for common data tasks and provide the history of each pipeline run, which is specific to the pipeline. Having a central place to manage all your pipelines is a critical step to having reliable, scalable data pipelines. So, this chapter will discuss these topics in detail and create more stability in our data platform.

In this chapter, we’re going to cover the following main topics:

  • Logging and monitoring with Datadog
  • Secrets management
  • Databricks Workflows
  • Databricks REST APIs...
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