Data Warehousing on AWS (DWAWS) – Outline

Outline detalhado do curso

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 la