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Azure Data Engineering Cookbook
Azure Data Engineering Cookbook

Azure Data Engineering Cookbook: Get well versed in various data engineering techniques in Azure using this recipe-based guide , Second Edition

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Profile Icon Nagaraj Venkatesan Profile Icon Ahmad Osama
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Full star icon Full star icon Full star icon Full star icon Half star icon 4.6 (13 Ratings)
Paperback Sep 2022 608 pages 2nd Edition
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zł59.99 zł167.99
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Arrow left icon
Profile Icon Nagaraj Venkatesan Profile Icon Ahmad Osama
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Full star icon Full star icon Full star icon Full star icon Half star icon 4.6 (13 Ratings)
Paperback Sep 2022 608 pages 2nd Edition
eBook
zł59.99 zł167.99
Paperback
zł209.99
Subscription
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eBook
zł59.99 zł167.99
Paperback
zł209.99
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Table of content icon View table of contents Preview book icon Preview Book

Azure Data Engineering Cookbook

Securing and Monitoring Data in Azure Data Lake

Data Lake forms the key storage layer for data engineering pipelines. Security and the monitoring of Data Lake accounts are key aspects of Data Lake maintenance. This chapter will focus on configuring security controls such as firewalls, encryption, and creating private links to a Data Lake account. By the end of this chapter, you will have learned how to configure a firewall, virtual network, and private link to secure the Data Lake, encrypt Data Lake using Azure Key Vault, and monitor key user actions in Data Lake.

We will be covering the following recipes in this chapter:

  • Configuring a firewall for an Azure Data Lake account using the Azure portal
  • Configuring virtual networks for an Azure Data Lake account using the Azure portal
  • Configuring private links for an Azure Data Lake account
  • Configuring encryption using Azure Key Vault for Azure Data Lake
  • Accessing Blob storage accounts using managed identities
  • Creating an alert to monitor an Azure Data Lake account
  • Securing an Azure Data Lake account with an SAS using PowerShell

Configuring a firewall for an Azure Data Lake account using the Azure portal

Data Lake account access can be restricted to an IP or a range of IPs by whitelisting the allowed IPs in the storage account firewall. In this recipe, we'll learn to restrict access to a Data Lake account using a firewall.

Getting ready

Before you start, perform the following steps:

  1. Open a web browser and go to the Azure portal at https://portal.azure.com.
  2. Make sure you have an existing storage account. If not, create one using the Provisioning an Azure storage account using the Azure portal recipe in Chapter 1, Creating and Managing Data in Azure Data Lake.

How to do it…

To provide access to an IP or range of IPs, follow these steps:

  1. In the Azure portal, locate and open the Azure storage account. In our case, the storage account is packtadestoragev2, created in the Provisioning an Azure storage account using the Azure portal recipe of Chapter 1, Creating and Managing Data in Azure Data Lake.
  2. On the storage account page, in the Security + Networking section, locate and select Firewalls and virtual networks.

As the packtadestoragev2 account was created with public access, it can be accessed from all networks.

  1. To allow access from an IP or an IP range, click on the Selected networks option on the storage account on the Firewalls and virtual networks page:
Figure 2.1 – Azure Storage – Firewalls and virtual networks

Figure 2.1 – Azure Storage – Firewalls and virtual networks

  1. In the Selected networks option, scroll down to the Firewall section. To give access to your machine only, select the Add your client IP address option. To give access to a different IP or range of IPs, type in the IPs in the Address range section:
Figure 2.2 – The whitelist IPs in the Azure Storage Firewall section

Figure 2.2 – The whitelist IPs in the Azure Storage Firewall section

  1. To access storage accounts from Azure services such as Azure Data Factory and Azure Functions, check Allow Azure services on the trusted services list to access this storage account under the Exceptions heading.
  2. Click Save to save the configuration changes.

How it works…

Firewall settings are used to restrict access to an Azure storage account to an IP or range of IPs. Even if a storage account is public, it will only be accessible to the whitelisted IPs defined in the firewall configuration.

Configuring virtual networks for an Azure Data Lake account using the Azure portal

A storage account can be public which is accessible to everyone, public with access to an IP or range of IPs, or private with access to selected virtual networks. In this recipe, we'll learn how to restrict access to an Azure storage account in a virtual network.

Getting ready

Before you start, perform the following steps:

  1. Open a web browser and go to the Azure portal at https://portal.azure.com.
  2. Make sure you have an existing storage account. If not, create one using the Provisioning an Azure storage account using the Azure portal recipe in Chapter 1, Creating and Managing Data in Azure Data Lake.

How to do it…

To restrict access to a virtual network, follow the given steps:

  1. In the Azure portal, locate and open the storage account. In our case, it's packtadestoragev2. On the storage account page, in the Security + Network section, locate and select Firewalls and virtual networks | Selected networks:
Figure 2.3 – Azure Storage – Selected networks

Figure 2.3 – Azure Storage – Selected networks

  1. In the Virtual networks section, select + Add new virtual network:
Figure 2.4 – Adding a virtual network

Figure 2.4 – Adding a virtual network

  1. In the Create virtual network blade, provide the virtual network name, Address space details, and Subnet address range. The remainder of the configuration values are pre-filled, as shown in the following screenshot:
Figure 2.5 – Creating a new virtual network

Figure 2.5 – Creating a new virtual network

  1. Click on Create to create the virtual network. This is created and listed in the Virtual Network section, as shown in the following screenshot:
Figure 2.6 – Saving a virtual network configuration

Figure 2.6 – Saving a virtual network configuration

  1. Click Save to save the configuration changes.

How it works…

We first created an Azure virtual network and then added it to the Azure storage account. Creating the Azure virtual network from the storage account page automatically fills in the resource group, location, and subscription information. The virtual network and the storage account should be in the same location.

The address space specifies the number of IP addresses in a given virtual network.

We also need to define the subnet within the virtual network that the storage account will belong to. We can also create a custom subnet. In our case, for the sake of simplicity, we have used the default subnet.

This allows the storage account to only be accessed by resources that belong to the given virtual network. The storage account is inaccessible to any network other than the specified virtual network.

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Key benefits

  • Build data pipelines from scratch and find solutions to common data engineering problems
  • Learn how to work with Azure Data Factory, Data Lake, Databricks, and Synapse Analytics
  • Monitor and maintain your data engineering pipelines using Log Analytics, Azure Monitor, and Azure Purview

Description

The famous quote 'Data is the new oil' seems more true every day as the key to most organizations' long-term success lies in extracting insights from raw data. One of the major challenges organizations face in leveraging value out of data is building performant data engineering pipelines for data visualization, ingestion, storage, and processing. This second edition of the immensely successful book by Ahmad Osama brings to you several recent enhancements in Azure data engineering and shares approximately 80 useful recipes covering common scenarios in building data engineering pipelines in Microsoft Azure. You’ll explore recipes from Azure Synapse Analytics workspaces Gen 2 and get to grips with Synapse Spark pools, SQL Serverless pools, Synapse integration pipelines, and Synapse data flows. You’ll also understand Synapse SQL Pool optimization techniques in this second edition. Besides Synapse enhancements, you’ll discover helpful tips on managing Azure SQL Database and learn about security, high availability, and performance monitoring. Finally, the book takes you through overall data engineering pipeline management, focusing on monitoring using Log Analytics and tracking data lineage using Azure Purview. By the end of this book, you’ll be able to build superior data engineering pipelines along with having an invaluable go-to guide.

Who is this book for?

This book is for data engineers, data architects, database administrators, and data professionals who want to get well versed with the Azure data services for building data pipelines. Basic understanding of cloud and data engineering concepts will help in getting the most out of this book.

What you will learn

  • Process data using Azure Databricks and Azure Synapse Analytics
  • Perform data transformation using Azure Synapse data flows
  • Perform common administrative tasks in Azure SQL Database
  • Build effective Synapse SQL pools which can be consumed by Power BI
  • Monitor Synapse SQL and Spark pools using Log Analytics
  • Track data lineage using Microsoft Purview integration with pipelines

Product Details

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Publication date : Sep 26, 2022
Length: 608 pages
Edition : 2nd
Language : English
ISBN-13 : 9781803246789
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Publication date : Sep 26, 2022
Length: 608 pages
Edition : 2nd
Language : English
ISBN-13 : 9781803246789
Vendor :
Microsoft
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Tools :

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Table of Contents

15 Chapters
Chapter 1: Creating and Managing Data in Azure Data Lake Chevron down icon Chevron up icon
Chapter 2: Securing and Monitoring Data in Azure Data Lake Chevron down icon Chevron up icon
Chapter 3: Building Data Ingestion Pipelines Using Azure Data Factory Chevron down icon Chevron up icon
Chapter 4: Azure Data Factory Integration Runtime Chevron down icon Chevron up icon
Chapter 5: Configuring and Securing Azure SQL Database Chevron down icon Chevron up icon
Chapter 6: Implementing High Availability and Monitoring in Azure SQL Database Chevron down icon Chevron up icon
Chapter 7: Processing Data Using Azure Databricks Chevron down icon Chevron up icon
Chapter 8: Processing Data Using Azure Synapse Analytics Chevron down icon Chevron up icon
Chapter 9: Transforming Data Using Azure Synapse Dataflows Chevron down icon Chevron up icon
Chapter 10: Building the Serving Layer in Azure Synapse SQL Pool Chevron down icon Chevron up icon
Chapter 11: Monitoring Synapse SQL and Spark Pools Chevron down icon Chevron up icon
Chapter 12: Optimizing and Maintaining Synapse SQL and Spark Pools Chevron down icon Chevron up icon
Chapter 13: Monitoring and Maintaining Azure Data Engineering Pipelines Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

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Full star icon Full star icon Full star icon Full star icon Half star icon 4.6
(13 Ratings)
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4 star 7.7%
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1 star 7.7%
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Ayman Dec 13, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This book is very similar to a cookbook indeed. You look up the "recipe" for what you're trying to accomplish in Azure regarding Data Engineering workloads and you'll find the step by step instructions. This book is not meant to be exhaustive on theory but rather how to implement solutions. It's on my shelf as a quick reference and review for something I need to get done. Many of the examples are both shown through the portal and via some sort of code (PowerShell, SQLCMD, KQL, etc). It's a great way to learn how to do the tasks multiple ways. If you're looking to get hands on and practice Data Engineering tasks and setup for the supporting environment in Azure, this is a great reference.
Amazon Verified review Amazon
Jagjeet S Makhija Nov 07, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I just finished the book Azure Data Engineering by Example: Practical Implementation for Data Engineers by both the authors. The book was exactly what I was expecting. The book itself is great and an introduction to Azure Data Engineering and it covers almost anything you need to know about Batch and Streaming Analytics. Like the excellent Azure Data book: Problem, Design, Solution. But this was only not the case, it’s a self-explanatory book about ADF, Azure Synapse, Power Shell, Query Optimization and it starts from scratch. The example part in the title is because all of the concepts are very well explained through examples. If you want to follow along, you need to read the book from front to cover, as they build upon each other. It’s a great introduction and although I was already familiar with most of the concepts, I definitely picked up a few things along the way. Especially the later chapters, about Migration SSIS packages, Configuring Azure Data Bricks environment, Delta Lake, transform data using Python and Scala were very interesting to me.This book is Impressive in my point of view!!
Amazon Verified review Amazon
Sivashankar G Oct 28, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
*Sharing your experience is much better than teaching just the theory*This is something I always believe, showing the way of doing it rather limiting the explanation only to the concept or theory is the better way of teaching. I love the way this book explains how a data engineer can use Azure data services, but more than that, how this shows the way of doing it using multiple ways.Another thing I noticed, and helped me to keep what I learnt in my head permanently, is “how it works” sections in this book. Absolutely a brilliant idea, not just limiting “how to do it”, extending it with “how it works” that helps us to understand how my implementation works, is something I really appreciate.I highly recommend this book for all data engineers who work with Azure or who plan to work with Azure. The Azure Data Engineering Cookbook is a one you must read.
Amazon Verified review Amazon
Gregory Smith Aug 19, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I've been meaning to write this book review for a while now – I got my hands on this book about five months back. To sum it up, going through the recipe examples has been a really enjoyable experience.For those of you aiming to rock the "Exam DP-203: Data Engineering on Microsoft Azure" and also wanting to get a good grip on exploring data, as well as setting up and managing secure and compliant data processing pipelines using all sorts of tools and tricks, this book is like your trusty sidekick. It'll help you build that strong foundation you need for the tough exam!"Azure Data Engineering Cookbook" is strategically tailored to cater to a diverse audience, ranging from database administrators, developers, to ETL practitioners. Through a pragmatic and recipe-centered approach, the book delves deep into the realm of Azure Data Engineering. Those versed in technical and database architecture, with a background in crafting data and ETL solutions within diverse environments including on-premise and other cloud platforms, will discover valuable insights within these pages.Just a heads-up, though: they assume you've got the basics of Azure and data engineering down, so you can dive right into the deep end of Azure Data Engineering without any hiccups.Grab a copy today!!
Amazon Verified review Amazon
Om S Dec 07, 2022
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Azure data engineering cookbook is a very practical book updated as the second edition that covers many dimensions of azure the data engineering process so called "reader with recipes" or hands-on chapters one step after another by beginning with Azure Data Lake and covering data ingestion using Azure Data Factory into Azure Data Lake and Azure SQL Database, management of common storage layers such as Azure Data Lake and Azure SQL Database, focusing on topics such as security, high availability, and performance monitoring.The center of the book is on data processing using Azure Databricks, Azure Synapse Analytics Spark pools, Synapse dataflows, and data exploration using Synapse serverless SQL pools this also focuses on the consumption of the data using Synapse dedicated SQL pool and Synapse Spark lake databases, covering the tips and tricks to optimize and maintain Synapse dedicated SQL pool databases and lake databases. Eventually, the bibliophile also has a reward chapter on managing the overall data engineering pipeline, which covers pipeline monitoring using Azure Log Analytics and following data lineage using Microsoft Purview.The book contains many helpful PowerShell scripts/Codes and distinctive screenshots, best way to get the most out of this is to go through one chapter at a time but even before that download code and files it starts from "Chapter04".For those who want to pass "Exam DP-203: Data Engineering on Microsoft Azure" and want to understand the data through exploration, build and maintain secure and compliant data processing pipelines by using different tools and techniques this book is their best friend. Make your foundation for the tough exam!
Amazon Verified review Amazon
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