In this Building Data Lakes on AWS course, you will learn how to build an operational data lake that supports the analysis of both structured and unstructured data. You will learn the components and functionality of the services involved in creating a data lake. You will use AWS Lake Formation to build a data lake, AWS Glue to build a data catalog, and Amazon Athena to analyze data. The course lectures and labs further your learning with the exploration of several common data lake architectures.
Building Data Lakes on AWS Delivery Methods
Building Data Lakes on AWS Course Information
In this Building Data Lakes on AWS course, you will learn how to:
- Apply data lake methodologies in planning and designing a data lake.
- Articulate the components and services required for building an AWS data lake.
- Secure a data lake with appropriate permission.
- Ingest, store, and transform data in a data lake.
- Query, analyze, and visualize data within a data lake.
Building Data Lakes on AWS Prerequisites
We recommend that attendees of this course have:
- Completed the AWS Technical Essentials classroom course.
- One year of experience building data analytics pipelines or have completed the Data Analytics Fundamentals digital course.
Building Data Lakes on AWS Training Outline
- Describe the value of data lakes
- Compare data lakes and data warehouses
- Describe the components of a data lake
- Recognize common architectures built on data lakes
- Describe the relationship between data lake storage and data ingestion
- Describe AWS Glue crawlers and how they are used to create a data catalog
- Identify data formatting, partitioning, and compression for efficient storage and query
Lab 1: Set up a simple data lake
- Recognize how data processing applies to a data lake
- Use AWS Glue to process data within a data lake
- Describe how to use Amazon Athena to analyze data in a data lake
- Describe the features and benefits of AWS Lake Formation
- Use AWS Lake Formation to create a data lake
- Understand the AWS Lake Formation security model
Lab 2: Build a data lake using AWS Lake Formation
- Automate AWS Lake Formation using blueprints and workflows
- Apply security and access controls to AWS Lake Formation
- Match records with AWS Lake Formation FindMatches
- Visualize data with Amazon QuickSight
Lab 3: Automate data lake creation using AWS Lake Formation blueprints
Lab 4: Data visualization using Amazon QuickSight
- Post course knowledge check
- Architecture review
- Course review