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AWS Authorized Training Course - Data Warehousing on AWS

Course Summary

Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift. This course demonstrates how to ingest, store, and transform data in the data warehouse. Topics covered include: the purpose of Amazon Redshift, how Amazon Redshift addresses business and technical challenges, features and capabilities of Amazon Redshift, designing a Data Warehousing Solution on AWS by applying best practices based on the Well-Architected Framework, integration with AWS and non-AWS products and services, performance tuning, orchestration, and securing and monitoring Amazon Redshift.

Prerequisites:

We recommend that attendees of this course have completed the following courses:

  • Fundamentals of Analytics on AWS – Part 1 (Digital course)• Fundamentals of Analytics on AWS – Part 2 (Digital course)
  • Building Data Lakes on AWS (Instructor led Training)
  • Building Data Analytics Solutions Using Amazon Redshift (Instructor led Training)

THIS COURSE IS NOT ELIGIBLE FOR TRAINING BUNDLES.

Purpose
How to design a cloud-based data warehousing solution using Amazon Redshift
Audience
Data Architects | Data Engineers | Database Administrators | Database Architects | Database Developers
Role
Data Architects | Data Engineers | Database Administrators | Database Architects | Database Developers
Skill Level
Intermediate
Style
Workshops
Duration
3 Days
Related Technologies
AWS | Data Warehouse | Amazon Redshift | ETL and ELT | Apache Airflow | Amazon Redshift ML

 

Course Objectives
  •  Describe Amazon Redshift architecture and its roles in a modern data architecture 
  • Design and implement a data warehouse in the cloud using Amazon Redshift 
  • Identify and load data into an Amazon Redshift data warehouse from a variety of sources 
  • Analyze data using SQL QEV2 notebooks 
  • Design and implement a disaster recovery strategy for an Amazon Redshift data warehouse 
  • Perform maintenance and performance tuning on an Amazon Redshift data warehouse 
  • Secure and manage access to an Amazon Redshift data warehouse 
  • Share data between multiple Redshift clusters in an organization 
  • Orchestrate workflows in the data warehouse using AWS Step Functions state machines 
  • Create an ML model and configure predictors using Amazon Redshift ML

What You'll Learn:

In the AWS Authorized Training Course - Data Warehousing on AWS training course, you'll learn:
  • Module 1: Data Warehouse Concepts
    • Modern data architecture 
    • Introduction to the course story 
    • Data warehousing with Amazon Redshift 
    • Amazon Redshift Serverless architecture 
    • Hands-On Lab: Launch and Configure an Amazon Redshift Serverless Data Warehouse 
  • Module 2: Setting up Amazon Redshift 
    • Data models for Amazon Redshift 
    • Data management in Amazon Redshift 
    • Managing permissions in Amazon Redshift 
    • Hands-On Lab: Setting up a Data Warehouse using Amazon Redshift Serverless 
  • Module 3: Loading Data 
    • Overview of data sources 
    • Loading data from Amazon Simple Storage Service (Amazon S3) 
    • Extract, transform, and load (ETL) and extract, load, and transform (ELT) 
    • Loading streaming data 
    • Loading data from relational databases 
    • Hands-On Lab: Populating the data warehouse
  • Module 4: Deep Dive into SQL Query Editor v2 and Notebooks 
    • Features of Amazon Redshift Query Editor v2 
    • Demonstration: Using Amazon Redshift Query Editor v2 
    • Advanced queries 
    • Hands-On Lab: Data Wrangling on AWS 
  • Module 5: Backup and Recovery 
    • Disaster recovery 
    • Backing up and restoring Amazon Redshift provisioned 
    • Backing up and restoring Amazon Redshift Serverless 
  • Module 6: Amazon Redshift Performance Tuning 
    • Factors that impact query performance 
    • Table maintenance and materialized views 
    • Query analysis 
    • Workload management 
    • Tuning guidance 
    • Amazon Redshift monitoring 
    • Hands-On Lab: Performance Tuning the Data Warehouse 
  • Module 7: Securing Amazon Redshift 
    • Introduction to Amazon Redshift security and compliance 
    • Authentication with Amazon Redshift 
    • Access control with Amazon Redshift 
    • Data encryption with Amazon Redshift
    • Auditing and compliance with Amazon Redshift 
    • Hands-On Lab: Securing Amazon Redshift 
  • Module 8: Orchestration 
    • Overview of data orchestration 
    • Orchestration with AWS Step Functions 
    • Orchestration with Amazon Managed Workflows for Apache Airflow (MWAA) 
    • Hands-On Lab: Orchestrating the Data Warehouse Pipeline 
  • Module 9: Amazon Redshift ML 
    • Machine Learning Overview 
    • Getting started with Amazon Redshift ML 
    • Amazon Redshift ML workflow scenarios 
    • Amazon Redshift ML Usage 
    • Hands-On Lab: Predicting customer churn with Amazon Redshift ML 
  • Module 10: Amazon Redshift Data Sharing 
    • Overview of data sharing in Amazon Redshift 
    • Amazon DataZone for Data as a service 
  • Module 11: Wrap-Up 
    • Hands-On Lab: End of course challenge lab
“I appreciated the instructor's technique of writing live code examples rather than using fixed slide decks to present the material.”

VMware

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