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Microsoft Certified Azure Data Fundamentals (Exam DP-900) Certification Guide

You're reading from   Microsoft Certified Azure Data Fundamentals (Exam DP-900) Certification Guide The comprehensive guide to passing the DP-900 exam on your first attempt

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Product type Paperback
Published in Nov 2022
Publisher Packt
ISBN-13 9781803240633
Length 300 pages
Edition 1st Edition
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Author (1):
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Marcelo Leite Marcelo Leite
Author Profile Icon Marcelo Leite
Marcelo Leite
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Table of Contents (21) Chapters Close

Preface 1. Part 1: Core Data Concepts
2. Chapter 1: Understanding the Core Data Terminologies FREE CHAPTER 3. Chapter 2: Exploring the Roles and Responsibilities in Data Domain 4. Chapter 3: Working with Relational Data 5. Chapter 4: Working with Non-Relational Data 6. Chapter 5: Exploring Data Analytics Concepts 7. Part 2: Relational Data in Azure
8. Chapter 6: Integrating Relational Data on Azure 9. Chapter 7: Provisioning and Configuring Relational Database Services in Azure 10. Chapter 8: Querying Relational Data in Azure 11. Part 3: Non-Relational Data in Azure
12. Chapter 9: Exploring Non-Relational Data Offerings in Azure 13. Chapter 10: Provisioning and Configuring Non-Relational Data Services in Azure 14. Part 4: Analytics Workload on Azure
15. Chapter 11: Components of a Modern Data Warehouse 16. Chapter 12: Provisioning and Configuring Large-Scale Data Analytics in Azure 17. Chapter 13: Working with Power BI 18. Chapter 14: DP-900 Mock Exam 19. Index 20. Other Books You May Enjoy

Tasks and tools for data engineer profiles

Data engineers have a key role in a modern data organization. It is a multidisciplinary role, so it needs knowledge of programming, data transformation, and mathematics, among other areas. To support these important activities, there are several open source and Azure-native tools to help data engineers perform their day-to-day operations.

Tasks of the data engineer

The following are some examples of tasks that are the responsibility of the data engineer:

  • Developing data ingestion pipelines
  • Setting connectivity standards in data sources with proper security and latency
  • Maintaining data pipelines creating scripts for data structures with versioning control
  • Applying modern data exploration languages and libraries to generate insights
  • Supporting database administrators in the necessary analytical database maintenance routines
  • Modeling and implementing data consumption structures aligned with the business area...
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