This course runs for a duration of 3 days.
The class will run daily from 6:30 AM PT to 2:30 PM PT.
Class Location: Virtual LIVE Instructor Led - Virtual Live Classroom.
Unlock the power of cloud-based data warehousing with the Data Warehousing on AWS course. This course equips you with the skills to design, implement, and optimize a robust data warehousing solution using Amazon Redshift. Explore Redshift’s architecture, best practices, and integration with AWS services. Learn about data ingestion, transformation, SQL analysis, disaster recovery, performance tuning, security, and access management. Dive into the potential of data sharing, workflow orchestration with Step Functions, and machine learning with Redshift ML.
Objectives
This course teaches you how to:
Audience
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
