AWS

My AWS work is about extending AI telemetry beyond the Microsoft stack. The core project is a Python Lambda → S3 → Athena → QuickSight pipeline designed to unify AI usage and operational data from sources that don't have native Power BI connectors — including AWS Bedrock, third-party AI tools, and custom internal systems. This pipeline is in active development and represents the next phase of the AI Insights Hub.

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Work examples

AI Telemetry Ingestion Pipeline

Python Lambda functions that pull AI usage data from multiple sources, land it in S3, and make it queryable via Athena — the data foundation for cross-tool AI reporting.

Athena → QuickSight Dashboards

QuickSight dashboards built on Athena queries, providing a cloud-native view of AI spend and usage data that complements the Power BI reporting layer.

Screenshots shown are placeholders. Built with synthetic data — original architecture, design, and analysis are my own work.