Curriculum
- 3 Sections
- 10 Lessons
- 3 Days
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- Day One3
- 1.1Module 1: Introduction to Data Warehousing Relational databases Data warehousing concepts The intersection of data warehousing and big data Overview of data management in AWS Hands-on lab 1: Introduction to Amazon Redshift
- 1.2Module 2: Introduction to Amazon Redshift Conceptual overview Real-world use cases Hands-on lab 2: Launching an Amazon Redshift cluster
- 1.3Module 3: Launching clusters Building the cluster Connecting to the cluster Controlling access Database security Load data Hands-on lab 3: Optimizing database schemas
- Day Two3
- 2.1Module 4: Designing the database schema Schemas and data types Columnar compression Data distribution styles Data sorting methods
- 2.2Module 5: Identifying data sources Data sources overview Amazon S3 Amazon DynamoDB Amazon EMR Amazon Kinesis Data Firehose AWS Lambda Database Loader for Amazon Redshift Hands-on lab 4: Loading real-time data into an Amazon Redshift database
- 2.3Module 6: Loading data Preparing Data Loading data using COPY Maintaining tables Concurrent write operations Troubleshooting load issues Hands-on lab 5: Loading data with the COPY command
- Day Three4
- 3.1Module 7: Writing queries and tuning for performance Amazon Redshift SQL User-Defined Functions (UDFs) Factors that affect query performance The EXPLAIN command and query plans Workload Management (WLM) Hands-on lab 6: Configuring workload management
- 3.2Module 8: Amazon Redshift Spectrum Amazon Redshift Spectrum Configuring data for Amazon Redshift Spectrum Amazon Redshift Spectrum Queries Hands-on lab 7: Using Amazon Redshift Spectrum
- 3.3Module 9: Maintaining clusters Audit logging Performance monitoring Events and notifications Lab 8: Auditing and monitoring clusters Resizing clusters Backing up and restoring clusters Resource tagging and limits and constraints Hands-on lab 9: Backing up, restoring and resizing clusters
- 3.4Module 10: Analyzing and visualizing data Power of visualizations Building dashboards Amazon QuickSight editions and features
Module 4: Designing the database schema Schemas and data types Columnar compression Data distribution styles Data sorting methods
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Module 6: Loading data Preparing Data Loading data using COPY Maintaining tables Concurrent write operations Troubleshooting load issues Hands-on lab 5: Loading data with the COPY command
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