AWS: Data Analytics

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AWS: Data Analytics

This course is part of Exam Prep (DEA-C01): AWS Certified Data Engineer - Associate Specialization

Instructor: Whizlabs Instructor

Included with

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3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

6 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

6 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Explore data integration services to integrate data from multiple sources for analytics and application development.
Manage data lake access permissions and share data within and outside your organization.
Describe a fully managed service to process and analyze streaming data at any scale in AWS.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

6 assignments

Taught in English

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This course is part of the Exam Prep (DEA-C01): AWS Certified Data Engineer - Associate Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 3 modules in this course

AWS: Data Analytics is the fourth course of Exam Prep (DEA-C01): AWS Certified Data Engineer - Associate Specialization. This course assists learners in configuring data integration services to discover, move, and integrate data from multiple sources for application development. Learners will explore a serverless, interactive analytics service to analyze petabytes of data in AWS. This course teaches learners to extract data from various sources using big data frameworks such as Apache Spark, Hive, or Presto. The course is divided into two modules and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 3:00-3:30 Hours of Video lectures that provide both Theory and Hands-On knowledge. Also, Graded and Ungraded Quizzes are provided with every module to test the ability of learners.

Module 1: Data Integration in AWS Module 2: Data Analytics and ML in AWS By the end of this course, a learner will be able to: - Examine data integration services to integrate data from multiple sources for analytics and application development. - Centrally manage data lake access permissions and share data within and outside your organization. - Describe a fully managed service to process and analyze streaming data at any scale in AWS. This course is intended for candidates who wish to enhance their skills in analyzing large and complex datasets and have basic hands-on experience in analytics and database services.

Welcome to Week 1 of the AWS: Data Analytics course. This week, you will be introduced to AWS Glue, a fully managed ETL service for customers to prepare and load their data for analytics. You will explore some basic components of AWS Glue such as AWS Glue Catalog, Crawlers, Classifiers, etc. By the end of the week, you will learn some advanced features of AWS Glue Data Quality and AWS Glue DataBrew.

What's included

9 videos2 readings2 assignments1 discussion prompt

9 videos Total 44 minutes

AWS Glue 10 minutes
AWS Glue Catalog 5 minutes
AWS Glue Crawlers and Classifiers 7 minutes
AWS Glue Jobs 4 minutes
AWS Glue Databases and AWS Glue Tables 3 minutes
AWS Glue Data Quality 5 minutes
AWS Glue API - Sensitive Data 3 minutes
AWS Glue Workflow 3 minutes
AWS Glue DataBrew 4 minutes

2 readings Total 20 minutes

Welcome to the Course 10 minutes
Overview: Data Integration in AWS 10 minutes

2 assignments Total 55 minutes

Data Integration in AWS - Assessment 30 minutes
AWS Glue - Knowledge Check 25 minutes

1 discussion prompt Total 10 minutes

Meet and Greet 10 minutes

Welcome to Week 2 of the AWS: Data Analytics course. This week, you will be introduced to Amazon Athena, an interactive analytics service built on open-source frameworks, that provides a simplified way to analyze petabytes of data where it lives. You will also learn Amazon EMR, a managed cluster platform that simplifies running big data frameworks, such as Apache Hadoop and Apache Spark. By the end of the week, you will perform data integration using Amazon EMR and AWS Glue.

What's included

9 videos1 reading2 assignments1 ungraded lab

9 videos Total 39 minutes

Amazon Athena 4 minutes
Amazon Athena with Glue 3 minutes
Amazon Athena with Hive Metastore 4 minutes
Amazon Redshift Spectrum with Glue Data Catalog 4 minutes
Athena CTAS 5 minutes
SQL with Athena 3 minutes
AWS Lake Formation 4 minutes
Amazon EMR 9 minutes
Amazon EMR with Glue Data Catalog 4 minutes

1 reading Total 10 minutes

Overview: Amazon Athena and Amazon EMR in AWS 10 minutes

2 assignments Total 55 minutes

Amazon Athena and Amazon EMR in AWS - Assessment 30 minutes
Amazon Athena and Amazon EMR- Knowledge Check 25 minutes

1 ungraded lab Total 45 minutes

Querying Data in S3 with Amazon Athena 45 minutes

Welcome to Week 3 of the AWS: Data Analytics course. This week, you will be introduced to Data Analytics and ML services in AWS. You will learn Amazon Kinesis, a fully managed service to process and analyze streaming data at scale. You will explore Amazon Managed Service for Apache Flink to transform and analyze streaming data in real-time using Apache Flink. With Amazon QuickSight, one can enhance data-driven organizations with unified business intelligence (BI) at scale. By the end of this week, you will learn Amazon SageMaker, a fully managed service that can help to build, train, and deploy ML models at scale using a single integrated development environment (IDE).

What's included

5 videos3 readings2 assignments

5 videos Total 35 minutes

Amazon Kinesis 10 minutes
Amazon Managed Service for Apache Flink 11 minutes
Amazon Managed Streaming for Apache Kafka 3 minutes
Amazon Sagemaker 3 minutes
Amazon QuickSight 8 minutes

3 readings Total 30 minutes

Overview: Data Analytics and ML in AWS 10 minutes
Course Conclusion 10 minutes
What next? 10 minutes

2 assignments Total 40 minutes

Data Analytics and ML in AWS - Assessment 25 minutes
Analytics and Machine Learning Concepts- Knowledge Check 15 minutes

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Instructor

Whizlabs Instructor

Whizlabs

143 Courses 110,181 learners

Offered by

Whizlabs

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To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

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