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Azure Data Factory Cookbook

You're reading from Azure Data Factory Cookbook Build ETL, Hybrid ETL, and ELT pipelines using ADF, Synapse Analytics, Fabric and Databricks

Product type Paperback

Published in Feb 2024

Publisher Packt

ISBN-13 9781803246598

Length 532 pages

Edition 2nd Edition

Tools

Azure

Concepts

Data Engineering

Authors (4):

Tonya Chernyshova

Xenia Ireton

Dmitry Foshin

Dmitry Anoshin

View More author details

Table of Contents (15) Chapters

Preface

1. Getting Started with ADF

2. Orchestration and Control Flow FREE CHAPTER

3. Setting Up Synapse Analytics

4. Working with Data Lake and Spark Pools

5. Working with Big Data and Databricks

6. Data Migration – Azure Data Factory and Other Cloud Services

7. Extending Azure Data Factory with Logic Apps and Azure Functions

8. Microsoft Fabric and Power BI, Azure ML, and Cognitive Services

9. Managing Deployment Processes with Azure DevOps

10. Monitoring and Troubleshooting Data Pipelines

11. Working with Azure Data Explorer

12. The Best Practices of Working with ADF

13. Other Books You May Enjoy

14. Index

Monitoring and Troubleshooting Data Pipelines

Azure Data Factory is an orchestration and integration tool that helps engineers transfer data between multiple data stores, both within and outside of the Microsoft Azure ecosystem. However, data integration is rarely straightforward, and errors can and do occur. In this chapter, we will introduce tools to help you manage and monitor your Azure Data Factory pipelines. You will learn where and how to find more information about what went wrong when a pipeline failed, how to debug a failed run, how to set up alerts that notify you when there is a problem, and how to identify problems with your integration runtimes.

The following is a list of the recipes in this chapter:

Monitoring pipeline runs and integration runtimes
Investigating failures – running pipelines in debug mode
Rerunning activities
Configuring alerts for your Azure Data Factory runs

The rest of the chapter is locked

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Authors (4)

Dmitry Foshin

Dmitry Foshin

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.

See other products by Dmitry Foshin

Xenia Ireton

Xenia Ireton

Xenia Ireton is a Senior Software Engineer at Microsoft. She has extensive knowledge in building distributed services, data pipelines and data warehouses.

See other products by Xenia Ireton

Dmitry Anoshin

Dmitry Anoshin

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.

See other products by Dmitry Anoshin

Tonya Chernyshova

Tonya Chernyshova

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.

See other products by Tonya Chernyshova

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