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Introduction to Designing Data Lakes on AWS

Approx. 14 hours to complete

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Course Summary

This course teaches the fundamentals of designing and implementing data lakes on AWS. You will learn how to build scalable and secure data lakes that can handle large amounts of data in various formats.

Key Learning Points

Learn how to design and implement data lakes on AWS
Understand how to store and manage data in various formats
Discover how to secure and manage access to your data lake

Learning Outcomes

Design and create a data lake on AWS
Implement data management best practices
Secure and manage access to your data lake

Prerequisites or good to have knowledge before taking this course

Basic understanding of AWS services
Familiarity with data management concepts

Course Difficulty Level

Intermediate

Course Format

Self-paced
Video lectures
Hands-on exercises

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Description

In this class, Introduction to Designing Data Lakes on AWS, we will help you understand how to create and operate a data lake in a secure and scalable way, without previous knowledge of data science! Starting with the "WHY" you may want a data lake, we will look at the Data-Lake value proposition, characteristics and components.

Designing a data lake is challenging because of the scale and growth of data. Developers need to understand best practices to avoid common mistakes that could be hard to rectify. In this course we will cover the foundations of what a Data Lake is, how to ingest and organize data into the Data Lake, and dive into the data processing that can be done to optimize performance and costs when consuming the data at scale. This course is for professionals (Architects, System Administrators and DevOps) who need to design and build an architecture for secure and scalable Data Lake components. Students will learn about the use cases for a Data Lake and, contrast that with a traditional infrastructure of servers and storage.

Knowledge

Where to start with a Data Lake?
How to build a secure and scalable Data Lake?
What are the common components of a Data Lake?
Why do you need a Data Lake and what it's value?

Outline

Week 1
Introduction to Designing Data Lakes in AWS
Meet the Instructors
Introduction to Week 1
Why Data Lakes
Characteristics of Data Lakes
Data Lakes Components
Comparison of a Data Lake to a Data Warehouse
Discussing Sample Data Lake Architectures
Course Welcome and Student Information
Pre-Course Survey
Data Lake Characteristics and Components
Data Lakes and Data Warehouses
Mid-Course Survey
Week 1 Quiz

Week 2
Introduction to Week 2
AWS Data Lake Related Services
Amazon S3
AWS Glue Data Catalog
AWS Services Used for Data Movement
AWS Services for Data Processing
AWS Services for Analytics
AWS Services for Predictive Analytics and Machine Learning
Introduction to AWS LakeFormation
Amazon S3 and Glue Data Catalog
Data Movement
EMR, Glue Jobs, Lambda, Kinesis Analytics, RedShift
AWS Lake Formation
Week 2 Quiz

Week 3
Introduction to Week 3
Use the Right Tool for the Job
Understanding Data Structure and When To Process Data
Data Streaming Ingestion With Kinesis Services
Batch Data Ingestion with AWS Transfer Family
Batch Data Ingestion with AWS Snow Family
Data Cataloging
Using Glue Crawlers
Reviewing the Ingestion Part in Data Lake Architectures
Diving Deep on Amazon Kinesis
Batch Data Ingestion with AWS Services
The Importance of Data Cataloging
Week 3 Quiz

Week 4
Introduction to Week 4
Data Prep and AWS Glue Jobs
File Optimizations
Using S3, Glue and Athena to Get Insights about NYC Taxi Data
Introduction to Data Lake Security
The Power of Data Visualization
Introduction to Amazon QuickSight
Amazon QuickSight Demo
Registry of Open Data on AWS
Course Wrap Up
Columnar Data Formats and Amazon Athena Optimizations
Security and Compliance
Data visualization, Amazon QuickSight
Registry of Open Data
Post-Course Survey
Week 4 Quiz
Final Assessment

Summary of User Reviews

Introduction to Designing Data Lakes in AWS is a highly recommended course with great content and valuable insights. Many users found the course to be informative and engaging, with clear explanations and practical examples of how to design data lakes in AWS.

Key Aspect Users Liked About This Course

The course provides practical examples and hands-on exercises, which help users to understand the concepts better.

Pros from User Reviews

Great content and valuable insights
Clear explanations and practical examples
Engaging and informative
Hands-on exercises for better understanding
Flexible schedule and self-paced learning

Cons from User Reviews

Some users found the course to be too basic
Not suitable for advanced users
Limited interaction with the instructor
No certification offered
Lacks depth in certain areas

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