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Building Data Lakes on AWS

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Building Data Lakes on AWS

This course is part of AWS Cloud Solutions Architect Professional Certificate

Instructors: Rafael Lopes +1 more

41,541 already enrolled

Included with

6 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

6 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Apply data lake methodologies in planning and designing a data lake.
Describe the components and services required for building an AWS data lake.
Compare the ways data can be ingested, stored, and transformed in a data lake.
Explain how to secure a data lake with appropriate permissions.

Skills you'll gain

Category: Machine Learning
Category: Data Sharing
Category: Data Infrastructure
Category: Data Cleansing
Category: Interactive Data Visualization
Category: Data Import/Export
Category: Data Warehousing
Category: Data Storage
Category: Data Management
Category: Data Architecture
Category: Data Science
Category: Data Access
Category: Data Governance
Category: Data Integration
Category: Data Transformation
Category: Data Engineering
Category: Data Processing

Tools you'll learn

Category: Query Languages
Category: Data Lakes

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

7 assignments

Taught in English

Build your Data Analysis expertise

This course is part of the AWS Cloud Solutions Architect Professional Certificate

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

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 from Amazon Web Services

There are 6 modules in this course

The fundamental-level course is typically designed for individuals with a basic understanding of data storage and processing concepts but little to no prior experience with building data lakes on AWS specifically. After a brief introduction to Data Lakes, we'll introduce data ingestion, cataloging and preparation, concluding with an overview of querying data with Amazon Athena. The course will continue with an AWS Lake Formation overview, including a hands-on lab where you'll build a data lake. We'll then introduce data processing and analytics leveraing AWS Glue before diving into automated data lake creatiokn using Lake Formation blueprints. Finally, we'll close with Modern Data Architectures on AWS with a lab that covers publishing and consuming data products as a service.

This module provides an overview of data lakes, their purpose, and how they differ from data warehouses. It also covers the components and architectures involved in data lakes.

What's included

5 videos1 reading2 assignments1 plugin

5 videosTotal 19 minutes

Course Introduction and Overview3 minutes
Module Objectives1 minute
Why Data Lakes?4 minutes
Data Lake vs Data Warehouse5 minutes
Components and Architectures6 minutes

1 readingTotal 2 minutes

Pre-Course Survey2 minutes

2 assignmentsTotal 60 minutes

Knowledge Check30 minutes
Pre-Assessment30 minutes

1 pluginTotal 15 minutes

Pre-Course Survey15 minutes

This module focuses on the processes of ingesting data into a data lake, cataloging the data, and preparing it for analysis. It covers topics such as data lake storage, data ingestion methods, crawling and cataloging data, data formatting, partitioning, compression, and querying data with Amazon Athena.

What's included

10 videos1 reading1 assignment1 plugin

10 videosTotal 46 minutes

Module Objectives1 minute
Data Lake Storage5 minutes
Data Ingestion7 minutes
Crawl and Catalog Data4 minutes
Demo: Creating and Running a Glue Crawler9 minutes
Formatting the Data in the Lake3 minutes
Partitioning, Compressing, and Compacting the Data in the Lake4 minutes
Query Data with Amazon Athena3 minutes
Demo: Querying CSV data with Amazon Athena3 minutes
Demo: Columnar data formats with Amazon Athena - a performance and cost comparison7 minutes

1 readingTotal 2 minutes

Mid-Course Survey2 minutes

1 assignmentTotal 30 minutes

Knowledge Check30 minutes

1 pluginTotal 15 minutes

Mid-Course Survey15 minutes

This module introduces AWS Lake Formation, a service that helps build and manage data lakes on AWS. It covers the basic permission model, and provides an overview of the service’s features and capabilities.

What's included

3 videos1 reading1 assignment1 app item

This module covers data transformation techniques and tools like AWS Glue for processing and analyzing data in the data lake. It includes hands-on demos and a technical talk on Glue and Athena Federated Queries.

What's included

7 videos1 assignment1 discussion prompt

7 videosTotal 37 minutes

Module Objectives1 minute
Data Transformation4 minutes
Data Processing with AWS Glue5 minutes
AWS Glue Jobs and Workflows3 minutes
Demo - Glue Databrew9 minutes
Demo - Glue Studio9 minutes
Tech Talk - Glue / Athena Federated Queries7 minutes

1 assignmentTotal 30 minutes

Knowledge Check 30 minutes

1 discussion promptTotal 10 minutes

AWS Glue10 minutes

This module explores advanced features and configurations of AWS Lake Formation, including blueprints, workflows, and fine-grained access control. It also covers data visualization with Amazon QuickSight.

What's included

5 videos1 assignment1 app item

This module introduces the concept of modern data architecture and its implementation on AWS. It covers data movement scenarios, data sharing models, and relevant readings.

What's included

6 videos3 readings1 assignment1 app item1 plugin

6 videosTotal 19 minutes

Module Objectives1 minute
Modern Data Architecture3 minutes
Data Movement Scenarios3 minutes
Data Sharing Models3 minutes
Tech Talk - What's your favorite data lake feature?6 minutes
Course Recap/Key Takeaways4 minutes

3 readingsTotal 22 minutes

Reading: Modern data architecture5 minutes
Reading: Data Movement Scenarios15 minutes
Post-Course Survey2 minutes

1 assignmentTotal 60 minutes

Post-Assessment60 minutes

1 app itemTotal 60 minutes

Lab 3: Publishing and Managing Data Product in AWS Lake Formation60 minutes

1 pluginTotal 15 minutes

Post-Course Survey15 minutes

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Instructors

Rafael Lopes

Amazon Web Services

22 Courses269,296 learners

Alex G.

Amazon Web Services

16 Courses113,966 learners

Offered by

Amazon Web Services

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Frequently asked questions

Yes, you will need a credit card to activate your AWS account.

Learners enrolled in the Verified Certificate path will receive a certificate upon successful completion of the course.

This course has discussion groups aligned to each week of the course. We encourage learners to ask questions or offer suggestions and feedback. AWS Instructors will monitor the discussion groups to answer questions specific to the exercises and topics covered in the course.

Earning an AWS Certification typically requires both knowledge and experience. While this course, if taken in isolation, will provide you with relevant information and skills, it likely will not equip you to earn an AWS Certification. For more information about AWS Certifications, including recommended training and experience requirements, visit aws.amazon.com/certification.

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.