Airton Leal Mar 16, 2024

This book serves as an indispensable guide for data engineers navigating the intricate landscape of Azure's data integration services. Authored by experts in the field, this book offers a comprehensive exploration of ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) pipelines, empowering readers with the knowledge and tools necessary to efficiently manage data workflows within Azure Data Factory. With a focus on practical solutions and real-world scenarios (that is the best part), the cookbook equips professionals with a range of recipes tailored to address common challenges encountered in data integration projects.From designing data pipelines to orchestrating complex workflows, each recipe in the book is meticulously crafted to provide actionable insights and step-by-step instructions. Whether you're a seasoned data engineer or a newcomer to Azure's ecosystem, the "Azure Data Factory Cookbook" offers a wealth of techniques and best practices to streamline your data integration processes. With its clear explanations and hands-on approach, this book is an invaluable resource for anyone seeking to harness the full potential of Azure Data Factory in building robust and scalable data solutions.

Amazon Verified review

Vivek Verma May 10, 2024

This book covers a lot of topics. Given the title of the book was about ADF, I was really suprised to see the breadth of topics that were covered. The subtitle is A data engineer's guide to building and managing ETL and ELT pipelines with data integration. And that gives a clue to the fact that the coverage is much, much broader than ADF.I was surprised to see so much coverage of pipelines in other places like Synapse Analytics, Fabric, etc. but more surprised to see coverage of HDInsight and big data concepts. I can't remember the last time I saw anyone using HDInsight. I always thought it was seriously over-hyped while it was being promoted, and still think the same way.It made more sense to see a bunch of coverage of Databricks, delta tables and integrating ADF with Azure Machine Learning, Azure Logic Apps, Azure Functions and more. They are relatively common areas of integration for ADF, along with migrating on-premises SSIS packages to ADF.

Amazon Verified review

Darnell Grantham Jr. Mar 04, 2024

Big Data, Data Warehouses and Data Flows are as crucial toan organization's operations as physical assets are and the new book,Azure Data Factory Cookbook written by authors, Dmitry Foshin,Dmitry Anoshin, Tonya Chenyhsova and Xenia Hertzenber provide the necessaryrecipes for successful ETL operations spanning 12 chapters.One may wonder why would Microsoft name this product the Azure Data Factory? Well consider raw dataand blobs as unrefined widgets. Just as in a factory, you process these widgets through a pipelinefor transformation in the refining process to the eventual packaging; data blobs and raw data isingested, extracted, transformed and stored into manageable tables or endpoints for further use.The main focus is ETL (Extract, Transform, Load) using the Microsoft Azure platformwhich contain services like Azure SQL, Azure Data Factory, Azure Data Fabric and PowerBi.To successfully follow along with each section's examples, it is recommended that the readercreate an Azure account which is free to do so.This book begins by giving an overall summary of what ADF provides and introduces ASA (Azure Synapse Analytics) as an alternative to ADF when larger data warehouses are being analyzed.with showing examples of ETL actions using the Data Factory Studio or the Copy Data Tool(CDT). Lookingat the examples in the Azure Data Factory Studio as well as Azure Fabric Canvass, I found similaritiesto SSIS or SSDT for those familiar with SQL Development. Data Flows using Pipelines was explainedusing multiple examples in each chapter and well designed data pipelines are reusable forcontinuous operation and executed on demand.The ADF Pipeline uses a set of JSON config files and consists of 90+ connectors for the facilitationof ETL functions. As I dove further into the book, what caught my interest was Chapter 8 where theauthors gave several recipes involving the integration of Microsoft Fabric with Power BI, AzureMachine Language Learning and Cognitive Services. Just as scripts can be used in ETL actionsin SSIS, Cell Editor in Data Fabric uses PySpark which is a hybrid of Python and Spark usedspecifically in the data flow pipeline process. DataFlow Gen2 is an additional component that Azure FabricData Factory introduces as an additional tool which users PowerQuery with at least 120 Microsoft connectors for the facilitation of Pipelines into a Data Lake where multiple tools, functions and tablescan be stored. Overall this is a great resource to add to your ETL toolkit and worth the time and effort to follow these recipes along.

Amazon Verified review

Steven Fernandes Mar 02, 2024

This guide is a valuable resource for data engineers and architects exploring Azure's data processing capabilities, covering Azure Data Factory, Synapse, Databricks, Delta tables, and more. It offers insights into big data handling, migration of SSIS jobs to ADF, and integration with Azure services like ML and Logic Apps. However, its effectiveness is slightly marred by a confusing table of contents with sections like "Getting Read," "How to Do It...," and "How It Works...". A clearer, more intuitive organization would enhance its utility, making it easier for readers to navigate and locate specific information. Despite this, the book remains an indispensable tool for professionals aiming to build comprehensive data solutions in Azure.

Amazon Verified review

S.Kundu Apr 01, 2024

If you want to learn from the basics of how to create a data pipeline and integrate it with other Azure services along with discovering the benefits of cloud data warehousing, Azure Synapse Analytics, Azure Data Lake Storage and Databricks this book can be a one stop solution for you. It will also teach you the best practices of working with ADF.A few important topics of the book that I want to highlight are as below:The book starts with an introduction ADF and will teach you how to create ADF using UI, Copy Data Tool, Python, Powershell, Azure Bicep and different Templates. It will also cover how to create and configure linked services and datasets along with using different Data Factory activities such as GetMetaData, ForEach, Filter, Lookup, Web, Execute Pipeline, etc.The book will also guide you to setup Synapse Analytics workspace. You will load data to Azure Synapse using Azure Data Factory, Azure Data Studio, Bulk load options. You will learn about Dedicated SQL pool and serverless SQL pool along with how to work with Azure Purview using Azure Synapse.Then it will teach you how to create a Synapse Analytics Spark pool and integrate Azure Data Lake and run Spark pool jobs. You will be building and orchestrating a data pipeline for Data Lake using SparkThe book will then help you in setting up a HDInsight cluster, build a pipeline and deploy it to ADF. Then it will teach you to build data models in Delta Lake and data pipeline jobs in Databricks. You will also perform external integrations with other compute engines such as SnowflakeThen the book will cover the topic of how to perform Data Migration and help you understand how you can copy data from Amazon S3 to Azure Blob storage, copy large datasets from S3 to ADLS, copy data from Google Cloud Storage to Azure Data Lake, copy data from Google BigQuery to Azure data lake Storage and migrate data from Google BigQuery to Azure Synapse.It will also explain how to use Logic Apps and Azure Functions in ADF along with covering the topics of Microsoft Fabric, Power BI, Azure ML and Cognitive Services. You will be loading data with Microsoft Fabric Dataflows, building ML models with speed and scale, analyzing and transforming data with Azure AI and prebuilt ML models.Finally it will teach you how you can manage deployment processes with Azure DevOps and how to Monitor and Troubleshoot your Data Pipelines along with covering the Azure Data Explorer (ADX) which is a fast and highly scalable data exploration service for log and telemetry data.

Amazon Verified review

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

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