"Your training approach should be less theoretical and more focused on immediate, high-impact wins that demonstrate value if you want your team to begin utilizing new Amazon Redshift capabilities within 30 days. Start with a launch session that includes a live demonstration of the new features, such as AI-based query optimization, materialized view refresh enhancements, or auto-copy from S3, and link each one to a real-world performance or cost issue that matters to your team. When people realize how it benefits them now rather than in the future, they are more likely to adopt.
Then, implement a 4-week micro-learning plan:
- Week 1: Overview and quick wins — 15-20 minute video session or live session, modeling how to utilize the new features within your existing workloads.
- Week 2: Hands-on labs — create a Redshift Sandbox environment, and have developers experiment with certain use cases (for example, setting up auto-vacuum tuning, testing AQUA cache performance).
- Week 3: Team challenge — run a Redshift optimization sprint, where analysts or SREs re-work workloads using new features, with goal of improving query speed and or reducing cost.
- Week 4: Review / feedback - Join a short retrospective call for success stories, blockers, and anything learned.
Use bite-sized information drops to support it all, such as internal wiki snippets that highlight a single feature at a time, brief Loom movies, or Slack recommendations. Additionally, designate Redshift champions for each team who can provide guidance, share dashboards, and respond to inquiries. Lastly, to demonstrate impact, monitor adoption using Redshift system tables or AWS CloudWatch data, such as the number of workloads transferred to RA3 nodes or the number of queries using the new syntax."