Real-time Analytics & BI Dashboard

The Problem

Legacy reporting dashboards had 30+ minute data latency. Reports were generated hourly via batch jobs. Operations and trading teams couldn't react to real-time issues — every decision was based on stale data. Business units had divergent definitions of key metrics, making cross-team reporting unreliable.

My Contribution

I defined the reporting requirements and KPI framework for this real-time analytics overhaul at a capital markets firm. I facilitated sessions with trading desk leads, operations managers, and compliance stakeholders to document exactly what data they needed, at what latency, and in what form. I standardized metric definitions across four business units, translated those requirements into technical specifications for the data engineering team, validated the data models against source system schemas, and ran structured UAT across all business units before cutover. I also designed the custom dashboards and reports to deliver actionable insights for investment banking operations.

The Solution

Requirements-led analytics: stakeholder workshops to define KPI taxonomy, metric standardization across business units, technical specification for pipeline and dashboard teams, source-to-target validation, and phased rollout with structured UAT.

Results

• Sub-second query latency on 1M+ events/sec
• 100+ concurrent users with <200ms updates
• Incident detection time: 30 minutes → 30 seconds
• Operations team decisions 40% faster
• $20B+ daily transaction volume handled

Tech Stack