DP-203: Processing in Azure Using Streaming Solutions

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Chris Behrens

2:16:27

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01 Introduction

001 Course Introduction.mp4

01:43

002 Introducing a Scalable Leaderboard Solution for All Your Games.mp4

03:51

1697733325985-DP-203 Study Guide Compressed.pdf

02 Developing a Stream Processing Solution

001 Identifying Azure Services for Stream Processing.mp4

09:19

002 Process Time Series Data.mp4

05:22

003 Demo Create a Stream Processing Solution by Using Stream Analytics and Azure Event Hubs.mp4

07:10

003 Direct link to the load generation script on GitHub.txt

005 Instructions for installing Azure Event Hubs Library into a Databricks cluster.txt

005 Process Data by Using Spark Structured Streaming.mp4

11:37

006 Demo Create Windowed Aggregates.mp4

13:20

008 Introducing Schema Drift.mp4

06:16

008 More on Input Validation in Azure Stream Analytics.txt

008 More on the Event Hub Schema Registry.txt

009 Demo Handle Schema Drift.mp4

03:47

010 Process within One Partition.mp4

06:35

011 Process Data across Partitions.mp4

10:57

012 Optimize Pipelines for Analytical or Transactional Purposes.mp4

07:31

014 More about Streaming Units on Microsoft Learn.txt

014 More about Throughput Units on Microsoft Learn.txt

014 Scale Resources.mp4

05:19

015 Demo Create Tests for Data Pipelines.mp4

03:52

016 Configure Checkpoints and Watermarking during Processing.mp4

05:40

017 Handling Late-Arriving Data.mp4

06:00

018 Handle Interruptions.mp4

04:16

019 Demo Configure Exception Handling.mp4

02:15

021 Demo Upsert Data.mp4

06:52

022 Replay Archived Stream Data.mp4

04:01

023 Section Recap.mp4

04:39

load-generator.ps1.txt

03 Conclusion

001 Course Summary.mp4

02:06

002 Conclusion and Whats Next.mp4

01:03

003 Exam Tips.mp4

02:56

1695663072892-M03-L03 Study Guide.pdf

Description

Learn about processing data streams using Azure Event Hubs, Stream Analytics, and Databricks to prepare for the DP-203 exam section: Develop a Stream Processing Solution.

What You'll Learn?

The recommended order of courses to prepare for the DP-203 Data Engineering on Microsoft Azure Certification are as follows: * Building an Azure Data Engineer Foundation * Data Ingestion and Preparation * Processing in Azure Using Batch Solutions * Processing in Azure Using Streaming Solutions * Secure, Monitor, and Optimize Data Storage and Processing Finally, use the Practice Exams to test your understanding for the Exam. In this course, Processing in Azure using Streaming Solutions, you will learn about processing data streams using Azure Event Hubs, Stream Analytics, and Databricks. The material covered in this course is what you need to know when preparing for the *Develop a Stream Processing Solution* section of the DP-203 exam. Processing data in a stream, instead of per batch, is particularly useful in scenarios where you need near-real time answers to queries as soon as new data points come in. Examples are detecting and preventing fraudulent transactions and monitoring social media comments. In Azure, there are three services you'll use when working with streaming data: * Azure Event Hubs for ingesting and buffering data * Azure Stream Analytics for processing and transforming datastreams * Azure Databricks for processing and transforming data streams In this course, you will learn how to work with these services to: * Ingest data from streaming data sources * How to write Stream Analytics queries that produce results based on query windows * Partition data streams for scale * Deal with adversity * And more If you are preparing to take the DP-203 exam, this course will help you get ready for the section on streaming data.

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Chris Behrens

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