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

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

By : Steve Miles
5 (2)
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Microsoft Certified Azure Data Fundamentals (DP-900) Exam Guide

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

5 (2)
By: Steve Miles

Overview of this book

Microsoft's Azure Data Fundamentals (DP-900) certification exam validates your expertise in core data concepts and Azure’s powerful data services capabilities. This comprehensive guide written by Steve Miles—a Microsoft Azure MVP and certified trainer with over 25 years of experience in cloud data services and 30+ certifications across major platforms—serves as your gateway to a future shaped by data and AI, regardless of your technical background. With the help of examples, you'll learn fundamental data concepts, including data representation, data storage options, and common workloads and gain clarity on the roles and responsibilities of key data professionals such as data administrators, engineers, and analysts. This guide covers all crucial exam domains, from data services capabilities of the Azure cloud platform to considerations for relational, non-relational, and analytics workloads, encompassing both Microsoft and open-source technologies. To supplement your exam prep, this book gives you access to a suite of online resources designed to boost your confidence, including mock tests, interactive flashcards, and invaluable exam tips By the end of this book, you’ll be fully prepared not only to pass the DP-900 exam but also to confidently tackle data solutions in Azure, setting a strong foundation for your data-driven career
Table of Contents (11 chapters)
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Summary

This chapter included complete coverage of the DP-900 Azure Data Fundamentals exam’s Describe Consideration for Real-Time Data Analytics skills measured area.

In this chapter, you gained a comprehensive understanding of real-time data analytics, focusing on the fundamental differences between batch and streaming data processing and the key Azure services that support real-time analytics.

You began by identifying the difference between batch and streaming data processing. Batch processing involves collecting and processing large volumes of data at scheduled intervals, making it ideal for tasks where immediate processing is unnecessary, such as end-of-day financial reporting. In contrast, streaming data processing handles data in real time, processing it as it arrives. It is crucial for applications that require immediate insights, such as monitoring network traffic or analyzing social media feeds.

The chapter also introduced you to the various Microsoft Azure...

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