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

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Dmitry Foshin Tonya Chernyshova

Azure Data Factory Cookbook

Dmitry Foshin, Tonya Chernyshova, Dmitry Anoshin , Xenia Ireton

$124.95 $99.70

Paperback

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English

Packt Publishing Limited
28 February 2024

Database design & theory; Data warehousing; Computer science; Information architecture

Data Engineers guide to solve real-world problems encountered while building and transforming data pipelines using Azure's data integration tool

Key Features

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

Book DescriptionThis 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

Who this book is forThis book is for ETL developers, data warehouse and ETL architects, software professionals, and anyone else who wants to learn about the common and not-so-common challenges faced while developing traditional and hybrid ETL solutions using Microsoft's Azure Data Factory. You’ll also find this book useful if you are looking for recipes to improve or enhance your existing ETL pipelines. Basic knowledge of data warehousing is a prerequisite.

By: Dmitry Foshin, Tonya Chernyshova, Dmitry Anoshin, Xenia Ireton
Imprint: Packt Publishing Limited
Country of Publication: United Kingdom
Edition: 2nd Revised edition
Dimensions: Height: 235mm, Width: 191mm,
ISBN: 9781803246598
ISBN 10: 1803246596
Pages: 532
Publication Date: 28 February 2024
Audience: General/trade , ELT Advanced
Format: Paperback
Publisher's Status: Active

Table of Contents Getting Started with ADF Orchestration and Control Flow Setting up Synapse Analytics Working with Data Lake and Spark Pools Working with Big Data and Databricks Data Migration – Azure Data Factory and Other Cloud Services Extending Azure Data Factory with Logic Apps and Azure Functions Microsoft Fabric and Power BI, Azure ML and Cognitive Services Managing Deployment Processes with Azure DevOps Monitoring and Troubleshooting Data Pipelines Working with Azure Data Explorer The Best Practices of Working with ADF

Dmitry Foshin is a business intelligence team leader, whose main goals are delivering business insights to the management team through data engineering, analytics, and visualization. He has led and executed complex full-stack BI solutions (from ETL processes to building DWH and reporting) using Azure technologies, Data Lake, Data Factory, Data Bricks, MS Office 365, PowerBI, and Tableau. He has also successfully launched numerous data analytics projects – both on-premises and cloud – that help achieve corporate goals in international FMCG companies, banking, and manufacturing industries. Tonya Chernyshova is an experienced Data Engineer with over 10 years in the field, including time at Amazon. Specializing in Data Modeling, Automation, Cloud Computing (AWS and Azure), and Data Visualization, she has a strong track record of delivering scalable, maintainable data products. Her expertise drives data-driven insights and business growth, showcasing her proficiency in leveraging cloud technologies to enhance data capabilities. Dmitry Anoshin is a data-centric technologist and a recognized expert in building and implementing big data and analytics solutions. He has a successful track record when it comes to implementing business and digital intelligence projects in numerous industries, including retail, finance, marketing, and e-commerce. Dmitry possesses in-depth knowledge of digital/business intelligence, ETL, data warehousing, and big data technologies. He has extensive experience in the data integration process and is proficient in using various data warehousing methodologies. Dmitry has constantly exceeded project expectations when he has worked in the financial, machine tool, and retail industries. He has completed a number of multinational full BI/DI solution life cycle implementation projects. With expertise in data modeling, Dmitry also has a background and business experience in multiple relation databases, OLAP systems, and NoSQL databases. He is also an active speaker at data conferences and helps people to adopt cloud analytics. Xenia Ireton is a Senior Software Engineer at Microsoft. She has extensive knowledge in building distributed services, data pipelines and data warehouses.