Building a Serverless Data Lake on AWS
Course description
In this course on Building A Serverless Data Lake On AWS, you will develop an operational data lake that allows the study of structured and unstructured data. You will gain knowledge of the elements and features of the services used to build a data lake. You will also create a data lake using AWS Lake Formation, a data catalog with AWS Glue, and data analysis with Amazon Athena. Your understanding is furthered by examining numerous typical data lake structures in the course lectures and laboratories.
Activities
This Building a Serverless Data Lake on AWS Training includes the following activities:
- Group Discussions
- Live Demonstrations
- Hands-On Labs
- Knowledge Checks
Course Objectives
Intended Audience
Prerequisites
Module Breakdown
Module 1: Introduction to data lakes
- 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
Module 2: Data ingestion, cataloging, and preparation
- 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
Module 3: Data processing and analytics
- 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
Module 4: Building a data lake with AWS Lake Formation
- 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
Module 5: Additional Lake Formation configurations
- 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
Module 6: Architecture and course review
- Post course knowledge check
- Architecture review
- Course review
FAQ's
Is Cloud Wizard Consulting an official AWS training partner?
Yes, we have been since 2015.
Who should take up this course?
You can take on this course if you belong to the following category of individuals:
- Data platform engineers
- Solutions architects
- IT professionals
What prior experience do you need for this course?
To qualify for taking up this course, you’ll need the following:
- Completed the AWS Technical Essentials classroom course
- 1 year of experience building data analytics pipelines or have completed the Data Analytics Fundamentals digital course
How do I enroll in this course?
To enroll in this course, choose the starting date and make an online payment. Once your payment is confirmed, our team will reach out to you.
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