Book Image

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

By : Marcelo Leite
5 (1)
Book Image

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

5 (1)
By: Marcelo Leite

Overview of this book

Passing the DP-900 Microsoft Azure Data Fundamentals exam opens the door to a myriad of opportunities for working with data services in the cloud. But it is not an easy exam and you'll need a guide to set you up for success and prepare you for a career in Microsoft Azure. Absolutely everything you need to pass the DP-900 exam is covered in this concise handbook. After an introductory chapter covering the core terms and concepts, you'll go through the various roles related to working with data in the cloud and learn the similarities and differences between relational and non-relational databases. This foundational knowledge is crucial, as you'll learn how to provision and deploy Azure's relational and non-relational services in detail later in the book. You'll also gain an understanding of how to glean insights with data analytics at both small and large scales, and how to visualize your insights with Power BI. Once you reach the end of the book, you'll be able to test your knowledge with practice tests with detailed explanations of the correct answers. By the end of this book, you will be armed with the knowledge and confidence to not only pass the DP-900 exam but also have a solid foundation from which to embark on a career in Azure data services.
Table of Contents (21 chapters)
1
Part 1: Core Data Concepts
7
Part 2: Relational Data in Azure
11
Part 3: Non-Relational Data in Azure
14
Part 4: Analytics Workload on Azure

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...