Note: This course is additionally enriched with content from the course Building Data Analytics Solutions 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.
Day 1
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
Day 2
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
Day 3
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