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Azure Data Engineer Associate Certification Guide

Azure Data Engineer Associate Certification Guide - Second Edition

By : Palmieri, Surendra Mettapalli, Alex
4.6 (16)
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Azure Data Engineer Associate Certification Guide

Azure Data Engineer Associate Certification Guide

4.6 (16)
By: Palmieri, Surendra Mettapalli, Alex

Overview of this book

One of the top global cloud providers, Azure offers extensive data hosting and processing services, driving widespread cloud adoption and creating a high demand for skilled data engineers. The Azure Data Engineer Associate (DP-203) certification is a vital credential, demonstrating your proficiency as an Azure data engineer to prospective employers. This comprehensive exam guide is designed for both beginners and seasoned professionals, aligned with the latest DP-203 certification exam, to help you pass the exam on your first try. The book provides a foundational understanding of IaaS, PaaS, and SaaS, starting with core concepts like virtual machines (VMs), VNETS, and App Services and progressing to advanced topics such as data storage, processing, and security. What sets this exam guide apart is its hands-on approach, seamlessly integrating theory with practice through real-world examples, practical exercises, and insights into Azure's evolving ecosystem. Additionally, you'll unlock lifetime access to supplementary practice material on an online platform, including mock exams, interactive flashcards, and exam tips, ensuring a comprehensive exam prep experience. By the end of this book, you’ll not only be ready to excel in the DP-203 exam, but also be equipped to tackle complex challenges as an Azure data engineer.
Table of Contents (17 chapters)
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1
Part 1: Azure Basics
3
Part 2: Data Storage
6
Part 3:Data Processing
11
Part 4:Secure, Monitor, and Optimize Data Storage and Processing

Creating Windowed Aggregates

Windowed aggregates are essential for processing time series data, which is simply data recorded continuously over time. Examples of time series data could include stock prices recorded over time and IoT sensor values, which show the health of machinery over time.

Note

This section primarily focuses on the Create windowed aggregates concept of the DP-203: Data Engineering on Microsoft Azure exam.

In the subsequent sections, you’ll explore the different windowed aggregates that are available in ASA. ASA supports the following five types of windows:

  • Tumbling Windows: These are fixed-size, non-overlapping windows where each window covers a specific time duration, and data is aggregated separately for each window.
  • Hopping windows: Similar to Tumbling Windows, hopping windows also have a fixed size, but they can overlap with each other. This allows more flexibility in capturing data and analyzing trends over time.
  • Sliding windows...
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