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Building Data Lakes on AWS [for Data Analysts] with DataBrew

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Tue, Dec 10, 2024, 9:00 AM – 5:00 PM EST
Dates Breakdown
Tue, Dec 10, 2024, 9:00 – 9:30 AM EST
Prerequisites review + data profiling demo
Tue, Dec 10, 2024, 9:30 – 10:00 AM EST
Module 1 - Introduction to data lakes + walkthrough demo
Building Data Lakes on AWS [for Data Analysts] with DataBrew

Building Data Lakes on AWS [for Data Analysts] with DataBrew

Complete and detailed coverage of the essentials - 1-Day hands-on training

Tuition: $1,195 (Early Bird Discount by NOV 21: $100 OFF | 4+ Group Discount: $500+ OFF)

After taking this course, you will be able 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


This course is designed primarily for data analysts, but could also benefit data scientists, data platform engineers, solution architects, and IT professionals who work with data.

Prerequisites: one year of experience building data analytics pipelines or have completed our instructor-led, AWS Data Analytics Fundamentals course.

Outline

Topics are covered in the order they appear, however some jumping back-and-forth is necessary to explore relevant topics at the time they are first encountered. Below is a list of topics that will be covered by module:

  • 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 DataBrew 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

Lab exercises are designed to cover one particular topic and help with learning retention.

Amazon Web Services and AWS are trademarks of Amazon.com, Inc. or its affiliates in the United States and/or other countries.

This course is compatible with AWS official curriculum.

Net Cirque is an AWS Consulting Partner.

AWS Partner Network

Instructors

George

Data Management Consultant

Contact us

Classifications

Categories
  • AWS Certified Data Analytics
  • Analytics Essentials Journey Series
Levels
  • Advanced
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