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.
Offered By


Introduction to Designing Data Lakes on AWS
Amazon Web ServicesAbout this Course
What you will learn
- 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?
Skills you will gain
- Data Science
- Analytics
- Big Data
- Data Lake
- Amazon Web Services (Amazon AWS)
Offered by

Amazon Web Services
Since 2006, Amazon Web Services has been the world’s most comprehensive and broadly adopted cloud platform. AWS offers over 90 fully featured services for compute, storage, networking, database, analytics, application services, deployment, management, developer, mobile, Internet of Things (IoT), Artificial Intelligence, security, hybrid and enterprise applications, from 44 Availability Zones across 16 geographic regions. AWS services are trusted by millions of active customers around the world — including the fastest-growing startups, largest enterprises, and leading government agencies — to power their infrastructure, make them more agile, and lower costs.
Syllabus - What you will learn from this course
Week 1
Welcome to the course! In Week 1, you'll discover why you may want a Data Lake, its characteristics and components, and how it compares to other data data scenarios, such as databases and data warehouses.
Week 2
in Week 2, you'll build on your knowledge of what data lakes are and why they may be a solution for your needs. You'll explore AWS services that can be used in data lake architectures, like Amazon S3, AWS Glue, Amazon Athena, Amazon Elasticsearch Service, LakeFormation, Amazon Rekognition, API Gateway and other services used for data movement, processing and visualization.
Week 3
In Week 3, you'll explore specifics of data cataloging and ingestion, and learn about services like AWS Transfer Family, Amazon Kinesis Data Streams, Kinesis Firehose, Kinesis Analytics, AWS Snow Family, AWS Glue Crawlers, and others. You'll also discover when is the right time to process data--before, after, or while data is being ingested. Given scenarios, you'll be able to easily identify when to process data and match the most appropriate AWS services to each scenario.
Week 4
In Week 4, you are going to dive deeper into data optimization and data processing. Demos around best practices will show you how to optimize your dataset for performance and cost--just by using the right tool for the job! You will also discover data security, data visualization tools, and AWS datasets you can use to experiment and get started.
Reviews
- 5 stars76.04%
- 4 stars15.62%
- 3 stars8.33%
TOP REVIEWS FROM INTRODUCTION TO DESIGNING DATA LAKES ON AWS
A very good first introductory course to data lakes and how to implement them using AWS services.
liked so far, good speed and good to know knowledge about the product offering and concepts.
Exactly beneficial for those who are seeking to understand the basics of data analytics services
Great course, great instructors, I learned a lot. Thanks.
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