Course Description
In this course, professionals will learn how to form an operational data lake that supports the analysis of both structured & unstructured data. You will learn the components & functionality of the services involved in creating a data lake. Professionals will use AWS Lake Formation to form a data lake, AWS Glue to form a data catalog, & Amazon Athena to analyze data. The course lectures & labs further you’re learning by exploring several common data lake architectures.
Prerequisites
We recommend that participants of this course have the following:
- Finished the AWS Technical Essentials classroom course
- One-year of experience building data analytics pipelines or have finished the Data Analytics Fundamentals digital course
Target Audience
This course is intended for:
- Data platform engineers
- Solutions architects
- IT professionals
Course Objectives
In this course, you will learn to:
- Apply data lake methodologies in planning & designing a data lake
- Articulate the components & services required for building an AWS data lake
- Secure a data lake with appropriate permission
- Ingest, store, & transform data in a data lake
- Query, analyze, & visualize data within a data lake
Content Outline
- Describe the value of data lakes
- Describe the components of a data lake
- Recognize common architectures built on data lakes
- Describe the relationship between data lake storage & data ingestion
- Describe AWS Glue crawlers & how they are used to create a data catalog
- Identify data formatting, partitioning, & compression for efficient storage & query
- Lab 1- Set up a simple data lake
- Identify how data processing applies to the data lake
- Use AWS Glue to process data within the data lake
- Explain how to use Amazon Athena to analyze data in a data lake
- Describe the features & merits of AWS Lake Formation
- Use AWS Lake Formation to form 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 & workflows
- Apply security & 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
FAQs
A data lake is a centralized & secured repository that piles all your data, both in its original form & prepared for analysis.
There are three methods of data storage, namely –
- Object storage
- File storage
- Block storage
EC2 is a service that enables business clients to run application programs in the computing environment.
AWS security provides opportunities to protect the data, check out security-related activity & receive automated responses.
Radiant believes in a practical & creative approach to training & development, which distinguishes it from other training & development platforms. Moreover, training courses are undertaken by some experts with a vast range of experience in their domain.
Radiant team of experts will be available at e-mail support@radianttechlearning.com to answer your technical queries after the training program.
Yes, Radiant will provide you most updated, high, value & relevant real-time projects & case studies in each training program.
Technical issues are unpredictable & might occur with us as well. Participants have to ensure they have access to the required configuration with good internet speed.
Radiant Tech learning offers training programs on weekdays, weekends & combination of weekdays & weekends. We provide you with complete liberty to choose the schedule that suits your needs.