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ETL with Azure Cookbook

You're reading from   ETL with Azure Cookbook Practical recipes for building modern ETL solutions to load and transform data from any source

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Product type Paperback
Published in Sep 2020
Publisher Packt
ISBN-13 9781800203310
Length 446 pages
Edition 1st Edition
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Authors (3):
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Christian Cote Christian Cote
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Christian Cote
Matija Lah Matija Lah
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Matija Lah
Madina Saitakhmetova Madina Saitakhmetova
Author Profile Icon Madina Saitakhmetova
Madina Saitakhmetova
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Toc

Table of Contents (12) Chapters Close

Preface 1. Chapter 1: Getting Started with Azure and SSIS 2019 2. Chapter 2: Introducing ETL FREE CHAPTER 3. Chapter 3: Creating and Using SQL Server 2019 Big Data Clusters 4. Chapter 4: Azure Data Integration 5. Chapter 5: Extending SSIS with Custom Tasks and Transformations 6. Chapter 6: Azure Data Factory 7. Chapter 7: Azure Databricks 8. Chapter 8: SSIS Migration Strategies 9. Chapter 9: Profiling data in Azure 10. Chapter 10: Manage SSIS and Azure Data Factory with Biml 11. Other Books You May Enjoy

Chapter 9: Profiling data in Azure

Data profiling is an important part of every data project. It helps the data modeler create an accurate data model and tells ETL developers what type of data we have and how clean the data is. It will also dictate the various transformations we should apply to it.

Data profiling can help us find what metrics we can derive from the source dataset and to what extent we need to change (transform) the data to meet business rules. It can also help us find data inconsistencies before starting the ETL phase and derive a valid data model based on the source dataset.

The process flow from data ingestion to reporting can be described with the following diagram:

Figure 9.1 – An overview of the data profiling process

This chapter will focus on the Profiling data step shown in the preceding diagram. Here, you will learn common techniques to achieve data profiling.

In this chapter, we will cover the following recipes:

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