I. Overview:

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.

II. Duration: 24 hours (3 days)

III. 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

IV. Intended Audience:

• Data engineers
• Data architects
• Database architects
• Database administrators
• Database developers.

V. Prerequisites:

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).

VI. Course outlines:

1. Module 1: Data Warehouse Concepts

• Overview
• Modern Data Architecture
• Introduction to the Course Story
• Data warehousing with Amazon Redshift
• Amazon Redshift Serverless architecture
• Instructor Demonstration: Creating an Amazon Redshift Serverless Data Warehouse
• Instructor Demonstration: Amazon Redshift Provisioned Architecture
• Knowledge Check
• Lab 1: Access and Examine Data with Amazon Redshift Serverless

2. Module 2: Setting Up Amazon Redshift

• Overview
• Data Models for Amazon Redshift
• Instructor Demonstration: Amazon Redshift Data Model
• Instructor Demonstration: Connecting to Amazon Redshift through AWS Secrets Manager
• Data Management
• Instructor Demonstration: Distribution Styles, Sort Keys, and Compression Encodings
• Managing Permissions
• Knowledge Check
• Lab 2: Setting Up a Data Warehouse Using Amazon Redshift Serverless

3. Module 3: Loading Data

• Overview
• Setting the Context
• Loading Data from Amazon S3
• Instructor Demonstration: Load Validation and Troubleshooting
• ETL and ELT
• Loading Streaming Data
• Loading Data from Relational Databases
• Instructor Demonstration: Aurora Zero-ETL
• Knowledge Check
• Lab 3: Populating the Data Warehouse

4. Module 4: Deep Dive into sql Query editor v2 and Notebooks

• Overview
• Features of Amazon Redshift query editor v2
• Instructor Demonstration: Using Amazon Redshift query editor v2
• Advanced Queries
• Instructor Demonstration: Aggregation Extensions
• Knowledge Check
• Lab 4: Data Wrangling for Amazon Redshift

5. Module 5: Disaster Recovery

• Overview
• Disaster recovery
• Instructor Demonstration: AWS Backup
• Knowledge Check

6. Module 6: Amazon Redshift Performance Tuning

• Overview
• Amazon Redshift Performance Tuning
• Table Maintenance and Materialized views
• Query Analysis
• Workload Management
• Amazon Redshift Monitoring
• Knowledge Check
• Lab 5: Performance Tuning the Data Warehouse

7. Module 7: Securing Amazon Redshift

• Overview
• Authentication with Amazon Redshift
• Access control with Amazon Redshift
• Instructor Demonstration: Amazon Redshift Row-Level Security
• Instructor Demonstration: Amazon Redshift Column-Level Security
• Instructor Demonstration: Amazon Redshift Data Masking
• Instructor Demonstration: Access Control with AWS Lake Formation
• Data encryption with Amazon Redshift
• Auditing and Compliance with Amazon Redshift
• Knowledge Check
• Lab 6: Securing Amazon Redshift

8. Module 8: Orchestration

• Overview
• Overview of Data Orchestration
• Orchestration with AWS Step Functions
• Orchestration with Amazon Managed Workflows for Apache Airflow
• Instructor Demonstration: Creating State Machines
• Knowledge Check
• Lab 7: Orchestrating the Data Warehouse Pipeline

9. Module 9: Amazon Redshift ML

• Overview
• Machine Learning Overview
• Knowledge Check
• Getting started with Amazon Redshift ML
• Amazon Redshift ML workflow scenarios
• Amazon Redshift ML Usage
• Knowledge Check
• Lab 8: Predicting Ticket Sales with Amazon Redshift ML

10. Module 10: Amazon Redshift Data Sharing

• Overview
• Overview of Data Sharing in Amazon Redshift
• Amazon DataZone for Data as a service
• Instructor Demonstration: Amazon DataZone
• Knowledge Check
• Challenge Lab: The Lifecycle of the Data Warehouse