Real-Time Data Pipelines & Analytics on AWS

Real-Time Data Pipelines & Analytics on AWS

本课程是 AWS Certified Data Engineer Associate Exam Prep 专项课程的一部分

位教师：LearnKartS

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2个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

8 小时完成

灵活的计划

自行安排学习进度

2个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

8 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Build real-time data pipelines with AWS tools like Kinesis, Glue, and Redshift.
Analyze and visualize streaming data using Athena, QuickSight, and OpenSearch.
Secure streams, scale clusters, and integrate Spark with AWS services.
Design production-ready pipelines for real-time business insights.

您将获得的技能

要了解的详细信息

可分享的证书

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作业

10 项作业

授课语言：英语（English）

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Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

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本课程是 AWS Certified Data Engineer Associate Exam Prep 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

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该课程共有2个模块

In today’s digital economy, data shouldn’t stand still — neither should you. This course, Real-Time Data Pipelines & Analytics on AWS, provides you with the necessary skills to process streaming data and make it business-ready. Taught with a focus on actual use cases, you get hands-on practice with AWS’s most popular tools, including Amazon Redshift, Kinesis, Glue, Athena, EMR, QuickSight, OpenSearch, and more.

Whether you are new to cloud data engineering or have experience and want to learn the latest, this course offers a curated curriculum featuring practical demos, guided videos, and examples. You’ll discover ways to increase the performance of your Redshift cluster, secure Kinesis streams, and integrate Spark with various AWS services. You’ll also be able to design analytics pipelines that provide real-time results. By the time you are finished with this course, you will be able to build production-ready data pipelines that shine in today’s high-demand tech industry. Enroll now and begin your path towards the data engineer that every company is looking for. Disclaimer: AWS and Amazon Web Services are trademarks of Amazon.com, Inc. or its affiliates. This course is not affiliated with or endorsed by AWS.

Learn to process and query large datasets with AWS services like Redshift and Apache Spark. Master data workflows, performance optimization, and Redshift integrations, including ML and Lambda UDFs.

涵盖的内容

12个视频3篇阅读材料4个作业

12个视频总计69分钟

Course Introduction 7分钟
Getting Started with Redshift 6分钟
Understanding Redshift Spectrum 6分钟
Boosting Query Performance in Redshift 7分钟
Exploring RA3 Nodes and Cross-Region Sharing 4分钟
Data Handling with Redshift Workflows 6分钟
Demo:Redshift Walkthrough 6分钟
Understanding Redshift ML 5分钟
Getting to Know Redshift Serverless 7分钟
Overview of Redshift Data API 5分钟
Overview of Apache Sparks 6分钟
Integrating Spark with AWS Data Services 6分钟

3篇阅读材料总计30分钟

Understanding Redshift’s Data Distribution 10分钟
Understanding Redshift Lambda UDFs 10分钟
Exploring Redshift System Tables 10分钟

4个作业总计65分钟

Introduction to Data Querying 12分钟
Advanced Data Processing 14分钟
Introduction to Data Querying 18分钟
Advanced Data Processing 21分钟

Dive into real-time data analytics with Kinesis, Athena, and AWS Glue for ETL tasks. Learn to process streaming data, scale real-time applications, and visualize data with QuickSight and MSK.