Developed and delivered realistic data assets to accelerate AWS SageMaker quickstart onboarding within the fiddler-examples repository. Focused on data engineering and machine learning operations, the work involved creating two comprehensive CSV datasets—home_price_baseline_data.csv and home_price_prod_data.csv—to support end-to-end model deployment and analysis workflows. The approach emphasized data readiness and demo preparation, ensuring that users could quickly engage with practical machine learning scenarios. No major bugs were addressed during this period, as efforts centered on provisioning high-quality, ready-to-use datasets and accompanying demo assets. This contribution enhanced customer onboarding by enabling immediate, hands-on experience with realistic business data in SageMaker workflows.