Building Data Lakes on AWS Course Overview

To ensure that participants are well-prepared and can fully benefit from the Building Data Lakes on AWS course, the following prerequisites are recommended:

• Basic understanding of database concepts, including traditional database management systems and SQL.
• Familiarity with the concept of data warehousing and the differences between structured and unstructured data.
• Some experience with cloud computing, particularly with Amazon Web Services (AWS), including an understanding of core AWS services such as Amazon S3, AWS Glue, Amazon Athena, and AWS Lake Formation is beneficial.
• Knowledge of data processing and analytics concepts, which will aid in understanding how data is transformed and analyzed within a data lake environment.
• Basic proficiency in using AWS Management Console and AWS Command Line Interface (CLI) will be helpful for the lab components of the course.
• A willingness to engage with hands-on lab exercises that reinforce the concepts taught in the lessons.

These prerequisites are intended to provide a foundation that will allow students to engage with the course content effectively. They are not meant to be barriers to entry, but rather to ensure that students have a positive and productive learning experience. Students with varying levels of prior knowledge have successfully completed the course by taking advantage of the resources provided and actively participating in the learning process.

Target Audience for Building Data Lakes on AWS

This AWS data lake course offers in-depth training on setting up and managing data lakes, ideal for IT professionals focused on data management and analytics.

• Data Engineers
• Data Scientists
• Data Analysts
• Cloud Architects
• IT Managers
• Database Administrators
• Big Data Specialists
• Business Intelligence Professionals
• System Administrators
• Developers interested in data lake architectures

Learning Objectives - What you will Learn in this Building Data Lakes on AWS?

Introduction to Learning Outcomes:

The Building Data Lakes on AWS course is designed to equip students with the skills needed to effectively construct, manage, and utilize data lakes on the AWS platform, focusing on concepts such as storage, processing, analysis, and security.

Learning Objectives and Outcomes:

• Understand the fundamental value and concepts of data lakes compared to traditional data warehouses.
• Learn the key components that constitute a data lake and explore common architectures integrating data lakes.
• Gain knowledge of data ingestion methods, cataloging with AWS Glue, and preparation techniques for optimal data storage and retrieval in AWS.
• Acquire hands-on experience in setting up a basic data lake on AWS through practical labs.
• Recognize the importance of data processing within a data lake and how to apply these concepts using AWS Glue.
• Learn to analyze data efficiently using Amazon Athena within a data lake environment.
• Explore the features, benefits, and security model of AWS Lake Formation for creating and managing data lakes.
• Gain practical skills in building a data lake using AWS Lake Formation through guided laboratory exercises.
• Understand how to automate data lake creation with AWS Lake Formation blueprints and workflows and enforce security and access controls.
• Develop the ability to match records and visualize data effectively using AWS Lake Formation FindMatches and Amazon QuickSight, respectively.