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Azure Data Engineering Cookbook

You're reading from   Azure Data Engineering Cookbook Design and implement batch and streaming analytics using Azure Cloud Services

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Product type Paperback
Published in Apr 2021
Publisher Packt
ISBN-13 9781800206557
Length 454 pages
Edition 1st Edition
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Authors (2):
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Nagaraj Venkatesan Nagaraj Venkatesan
Author Profile Icon Nagaraj Venkatesan
Nagaraj Venkatesan
Ahmad Osama Ahmad Osama
Author Profile Icon Ahmad Osama
Ahmad Osama
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Toc

Table of Contents (11) Chapters Close

Preface 1. Chapter 1: Working with Azure Blob Storage 2. Chapter 2: Working with Relational Databases in Azure FREE CHAPTER 3. Chapter 3: Analyzing Data with Azure Synapse Analytics 4. Chapter 4: Control Flow Activities in Azure Data Factory 5. Chapter 5: Control Flow Transformation and the Copy Data Activity in Azure Data Factory 6. Chapter 6: Data Flows in Azure Data Factory 7. Chapter 7: Azure Data Factory Integration Runtime 8. Chapter 8: Deploying Azure Data Factory Pipelines 9. Chapter 9: Batch and Streaming Data Processing with Azure Databricks 10. Other Books You May Enjoy

Chapter 9: Batch and Streaming Data Processing with Azure Databricks

Databricks is a data engineering product built on top of Apache Spark and provides a unified, cloud optimized platform so that you can perform ETL, machine learning, and AI tasks on a large quantity of data.

Azure Databricks, as its name suggests, is the Databricks integration with Azure, which further provides fully managed Spark clusters, an interactive workspace for data visualization and exploration, Azure Data Factory, integration with data sources such as Azure Blob Storage, Azure Data Lake Storage, Azure Cosmos DB, Azure SQL Data Warehouse, and more.

Azure Databricks can process data from multiple and diverse data sources, such as SQL or NoSQL, structured or unstructured data, and also scale up as many servers as required to cater to any exponential data growth.

In this chapter, we'll cover the following recipes:

  • Configuring the Azure Databricks environment
  • Transforming data using...
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