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Azure Data Factory Cookbook

You're reading from   Azure Data Factory Cookbook Build and manage ETL and ELT pipelines with Microsoft Azure's serverless data integration service

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Product type Paperback
Published in Dec 2020
Publisher Packt
ISBN-13 9781800565296
Length 382 pages
Edition 1st Edition
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Authors (4):
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Dmitry Anoshin Dmitry Anoshin
Author Profile Icon Dmitry Anoshin
Dmitry Anoshin
Roman Storchak Roman Storchak
Author Profile Icon Roman Storchak
Roman Storchak
Xenia Ireton Xenia Ireton
Author Profile Icon Xenia Ireton
Xenia Ireton
Dmitry Foshin Dmitry Foshin
Author Profile Icon Dmitry Foshin
Dmitry Foshin
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Toc

Table of Contents (12) Chapters Close

Preface 1. Chapter 1: Getting Started with ADF 2. Chapter 2: Orchestration and Control Flow FREE CHAPTER 3. Chapter 3: Setting Up a Cloud Data Warehouse 4. Chapter 4: Working with Azure Data Lake 5. Chapter 5: Working with Big Data – HDInsight and Databricks 6. Chapter 6: Integration with MS SSIS 7. Chapter 7: Data Migration – Azure Data Factory and Other Cloud Services 8. Chapter 8: Working with Azure Services Integration 9. Chapter 9: Managing Deployment Processes with Azure DevOps 10. Chapter 10: Monitoring and Troubleshooting Data Pipelines 11. Other Books You May Enjoy

Chapter 4: Working with Azure Data Lake

A data lake is a central storage system that stores data in its raw format. It is used to collect huge amounts of data that are yet to be analyzed by analysts and data scientists or for regulatory purposes. As the amount of information and the variety of data that a company operates with increases, it gets increasingly difficult to preprocess and store it in a traditional data warehouse. By design, data lakes are built to handle unstructured and semi-structured data with no pre-defined schema.

On-premise data lakes are difficult to scale and require thorough requirements and cost estimations. Cloud data lakes are often considered an easier-to-use and -scale alternative. In this chapter, we will go through a set of recipes that will help you to launch a data lake, load data from external storage, and build ETL/ELT pipelines around it.

Azure Data Lake Gen2 can store both structured and unstructured data. In this chapter, we will load...

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