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Azure Data Factory Cookbook - Second Edition
Azure Data Factory Cookbook - Second Edition

Azure Data Factory Cookbook: Build ETL, Hybrid ETL, and ELT pipelines using ADF, Synapse Analytics, Fabric and Databricks, Second Edition

Profile Icon Dmitry Foshin Profile Icon Tonya Chernyshova Profile Icon Dmitry Anoshin Profile Icon Xenia Ireton
By Dmitry Foshin , Tonya Chernyshova , Dmitry Anoshin , Xenia Ireton
Mex$631.99 Mex$902.99
Book Feb 2024 532 pages 2nd Edition
eBook
Mex$631.99 Mex$902.99
Print
Mex$1,128.99
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Profile Icon Dmitry Foshin Profile Icon Tonya Chernyshova Profile Icon Dmitry Anoshin Profile Icon Xenia Ireton
By Dmitry Foshin , Tonya Chernyshova , Dmitry Anoshin , Xenia Ireton
Mex$631.99 Mex$902.99
Book Feb 2024 532 pages 2nd Edition
eBook
Mex$631.99 Mex$902.99
Print
Mex$1,128.99
Subscription
Free Trial
eBook
Mex$631.99 Mex$902.99
Print
Mex$1,128.99
Subscription
Free Trial

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Azure Data Factory Cookbook - Second Edition

Orchestration and Control Flow

Azure Data Factory is an excellent tool for designing and orchestrating your Extract, Transform, Load (ETL) processes. In this chapter, we introduce several fundamental data factory concepts and guide you through the creation and scheduling of increasingly complex data-driven workflows. All the work in this chapter is done using the Microsoft data factory online portal. You’ll learn how to create and configure linked services and datasets, take advantage of built-in expressions and functions, and, most importantly, learn how and when to use the most popular Data Factory activities.

This chapter covers the following topics:

  • Using parameters and built-in functions
  • Using the Metadata and Stored Procedure activities
  • Using the ForEach and Filter activities
  • Chaining and branching activities within a pipeline
  • Using the Lookup, Web, and Execute Pipeline activities
  • Creating event-based pipeline triggers

Technical requirements

NOTE

To make fully understanding the recipes easier, we make naming suggestions for the accounts, pipelines, and so on throughout the chapter. Many services, such as Azure Storage and SQL Server, require that the names you assign are unique. Follow your own preferred naming conventions, making appropriate substitutions as you follow the recipes. For the Azure resource naming rules, refer to the documentation at https://learn.microsoft.com/en-us/azure/azure-resource-manager/management/resource-name-rules.

In addition to Azure Data Factory, we shall be using three other Azure services: Logic Apps, Blob Storage, and Azure SQL Database. You will need to have Azure Blob Storage and Azure SQL Database accounts set up to follow the recipes. The following steps describe the necessary preparation:

  • Create an Azure Blob Storage account and name it adforchestrationstorage. When creating the storage account, select the same region (that is, East US) as you selected when you created the Data Factory instance. This will reduce our costs when moving data.
  • Create a container named data within this storage account, and upload two CSV files to the folder: airlines.csv and countries.csv (the files can be found on GitHub: https://github.com/PacktPublishing/Azure-Data-Factory-Cookbook/tree/master/data).
  • Create an Azure SQL Database instance and name it AzureSQLDatabase. When you create the Azure SQL Database instance, you will have the option of creating a server on which the SQL database will be hosted. Create that server and take note of the credentials you entered. You will need these credentials later when you log in to your database.

Choose the basic configuration for your SQL server to save on costs. Once your instance is up and running, configure the Networking settings for the SQL server as highlighted in Figure 2.1. Go to the Networking page under the Security menu, then under Firewall rules, create a rule to allow your IP to access the database. Under Exceptions, make sure that you check the Allow Azure services and resources to access this database option.

Figure 2.1: Firewall configuration

Download the following SQL scripts from GitHub at https://github.com/PacktPublishing/Azure-Data-Factory-Cookbook/tree/master/Chapter02/sql-scripts:

  • CreateAirlineTable.sql and CreateCountryTable.sql: These scripts will add two tables, Country and Airline, which are used in several recipes, including the first one.
  • CreateMetadataTable.sql: This will create the FileMetadata table and a stored procedure to insert data into that table. This table is necessary for the Using Metadata and Stored Procedure activities and Filtering your data and looping through your files recipes.
  • CreateActivityLogsTable.sql: This will create the PipelineLog table and a stored procedure to insert data into that table. This table is necessary for the Chaining and branching activities within your pipeline recipe.
  • CreateEmailRecipients.sql: This script will create the EmailRecipients table and populate it with a record. This table is used in the Using the Lookup, Web, and Execute Pipeline activities recipe. You will need to edit it to enter email recipient information.

To create tables from the downloaded files, open your Azure SQL Database instance, go to the Query editor page, then paste the SQL scripts from the downloaded files and run them one by one.

Now that we’re all set up, let’s move on to the first recipe.

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Key benefits

  • Solve real-world data problems and create data-driven workflows with ease using Azure Data Factory
  • Build an ADF pipeline that operates on pre-built ML model and Azure AI
  • Get up and running with Fabric Data Explorer and extend ADF with Logic Apps and Azure functions

Description

This new edition of the Azure Data Factory book, fully updated to reflect ADS V2, will help you get up and running by showing you how to create and execute your first job in ADF. There are updated and new recipes throughout the book based on developments happening in Azure Synapse, Deployment with Azure DevOps, and Azure Purview. The current edition also runs you through Fabric Data Factory, Data Explorer, and some industry-grade best practices with specific chapters on each. You’ll learn how to branch and chain activities, create custom activities, and schedule pipelines, as well as discover the benefits of cloud data warehousing, Azure Synapse Analytics, and Azure Data Lake Gen2 Storage. With practical recipes, you’ll learn how to actively engage with analytical tools from Azure Data Services and leverage your on-premises infrastructure with cloud-native tools to get relevant business insights. You'll familiarize yourself with the common errors that you may encounter while working with ADF and find out the solutions to them. You’ll also understand error messages and resolve problems in connectors and data flows with the debugging capabilities of ADF. By the end of this book, you’ll be able to use ADF with its latest advancements as the main ETL and orchestration tool for your data warehouse projects.

What you will learn

  • Build and Manage data pipelines with ease using the latest version of ADF
  • Configure, load data, and operate data flows with Azure Synapse
  • Get up and running with Fabric Data Factory
  • Working with Azure Data Factory and Azure Purview
  • Create big data pipelines using Databricks and Delta tables
  • Integrate ADF with commonly used Azure services such as Azure ML, Azure Logic Apps, and Azure Functions
  • Learn industry-grade best practices for using Azure Data Factory

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Feb 28, 2024
Length 532 pages
Edition : 2nd Edition
Language : English
ISBN-13 : 9781803246598
Category :

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Product Details

Publication date : Feb 28, 2024
Length 532 pages
Edition : 2nd Edition
Language : English
ISBN-13 : 9781803246598
Category :

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Table of Contents

15 Chapters
Preface Chevron down icon Chevron up icon
1. Getting Started with ADF Chevron down icon Chevron up icon
2. Orchestration and Control Flow Chevron down icon Chevron up icon
3. Setting Up Synapse Analytics Chevron down icon Chevron up icon
4. Working with Data Lake and Spark Pools Chevron down icon Chevron up icon
5. Working with Big Data and Databricks Chevron down icon Chevron up icon
6. Data Migration – Azure Data Factory and Other Cloud Services Chevron down icon Chevron up icon
7. Extending Azure Data Factory with Logic Apps and Azure Functions Chevron down icon Chevron up icon
8. Microsoft Fabric and Power BI, Azure ML, and Cognitive Services Chevron down icon Chevron up icon
9. Managing Deployment Processes with Azure DevOps Chevron down icon Chevron up icon
10. Monitoring and Troubleshooting Data Pipelines Chevron down icon Chevron up icon
11. Working with Azure Data Explorer Chevron down icon Chevron up icon
12. The Best Practices of Working with ADF Chevron down icon Chevron up icon
13. Other Books You May Enjoy Chevron down icon Chevron up icon
14. Index Chevron down icon Chevron up icon
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