You're reading from Azure Databricks Cookbook Accelerate and scale real-time analytics solutions using the Apache Spark-based analytics service

Product type Paperback

Published in Sep 2021

Publisher Packt

ISBN-13 9781789809718

Length 452 pages

Edition 1st Edition

Languages

SQL

Tools

Azure

Concepts

Data Streaming

Authors (2):

Vinod Jaiswal

Phani Raj

View More author details

Table of Contents (12) Chapters

Preface

1. Chapter 1: Creating an Azure Databricks Service

2. Chapter 2: Reading and Writing Data from and to Various Azure Services and File Formats FREE CHAPTER

3. Chapter 3: Understanding Spark Query Execution

4. Chapter 4: Working with Streaming Data

5. Chapter 5: Integrating with Azure Key Vault, App Configuration, and Log Analytics

6. Chapter 6: Exploring Delta Lake in Azure Databricks

7. Chapter 7: Implementing Near-Real-Time Analytics and Building a Modern Data Warehouse

8. Chapter 8: Databricks SQL

9. Chapter 9: DevOps Integrations and Implementing CI/CD for Azure Databricks

10. Chapter 10: Understanding Security and Monitoring in Azure Databricks

11. Other Books You May Enjoy

Understanding the scenario for an end-to-end (E2E) solution

In this recipe, you will learn about an E2E solution that you will be building in this chapter. We will look at various components used in the solution and the data warehouse model that we will be creating in a Synapse dedicated pool.

Getting ready

You need to ensure you read the following chapters before starting on this recipe if you are new to Azure Databricks:

Chapter 2, Reading and Writing Data from and to Various Azure Services and File Formats
Chapter 4, Working with Streaming Data
Chapter 6, Exploring Delta Lake in Azure Databricks

Also, you will need to have a basic understanding of facts and dimension tables in a data warehouse.

How to do it…

In this section, you will understand an E2E data pipeline scenario along with the modern data warehouse model that will be created as part of the solution. The following points list down all the stages of the data pipeline, right from...