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Azure Data Engineer Associate Certification Guide

You're reading from   Azure Data Engineer Associate Certification Guide A hands-on reference guide to developing your data engineering skills and preparing for the DP-203 exam

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Product type Paperback
Published in Feb 2022
Publisher Packt
ISBN-13 9781801816069
Length 574 pages
Edition 1st Edition
Tools
Concepts
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Author (1):
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Newton Alex Newton Alex
Author Profile Icon Newton Alex
Newton Alex
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Toc

Table of Contents (23) Chapters Close

Preface 1. Part 1: Azure Basics
2. Chapter 1: Introducing Azure Basics FREE CHAPTER 3. Part 2: Data Storage
4. Chapter 2: Designing a Data Storage Structure 5. Chapter 3: Designing a Partition Strategy 6. Chapter 4: Designing the Serving Layer 7. Chapter 5: Implementing Physical Data Storage Structures 8. Chapter 6: Implementing Logical Data Structures 9. Chapter 7: Implementing the Serving Layer 10. Part 3: Design and Develop Data Processing (25-30%)
11. Chapter 8: Ingesting and Transforming Data 12. Chapter 9: Designing and Developing a Batch Processing Solution 13. Chapter 10: Designing and Developing a Stream Processing Solution 14. Chapter 11: Managing Batches and Pipelines 15. Part 4: Design and Implement Data Security (10-15%)
16. Chapter 12: Designing Security for Data Policies and Standards 17. Part 5: Monitor and Optimize Data Storage and Data Processing (10-15%)
18. Chapter 13: Monitoring Data Storage and Data Processing 19. Chapter 14: Optimizing and Troubleshooting Data Storage and Data Processing 20. Part 6: Practice Exercises
21. Chapter 15: Sample Questions with Solutions 22. Other Books You May Enjoy

Download the color images

We also provide a PDF file that has color images of the screenshots and diagrams used in this book. You can download it here: https://static.packt-cdn.com/downloads/9781801816069_ColorImages.pdf.

Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in the text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "And, finally, query from the star schema tables. Here is a sample query to get a list of all those customers whose end location was 'San Jose'."

A block of code is set as follows:

SELECT trip.[tripId], customer.[name] FROM 
dbo.FactTrips AS trip
JOIN dbo.DimCustomer AS customer
ON trip.[customerId] = customer.[customerId] 
WHERE trip.[endLocation] = 'San Jose';

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

df = spark.createDataFrame(data= driverData, schema = columnNames)
df.write.partitionBy("gender","salary")..parquet("abfss://path/to/output/")

Any command-line input or output is written as follows:

az vm extension set \
  --resource-group <YOUR_RESOURCE_GROUP> \
  --vm-name <VM_NAME> \
  --name OmsAgentForLinux \
  --publisher Microsoft.EnterpriseCloud.Monitoring \
  --protected-settings '{"workspaceKey":"<YOUR_WORKSPACE_KEY>"}' \
  --settings '{"workspaceId":"<YOUR_WORKSPACE_ID>"}'

Bold: Indicates a new term, an important word, or words that you see on screen. For instance, words in menus or dialog boxes appear in bold. Here is an example: "You can see that the data in the top table is distributed horizontally based on the Trip ID range."

Tips or Important Notes

Appear like this.

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