Financial Analytics Dashboard
FinTech · Analytics
2024
web
What they needed
The firm's analysts were stuck waiting on reports that couldn't keep pace with the business. The platform had to ingest and render over 10 million data points a day from live financial feeds, then let analysts drill into specific segments and time windows without a page reload. Standard charting approaches buckled at that volume — a single interactive chart could take seconds to draw, and keeping it live as the underlying data changed made the lag worse. Executives needed a firm-wide view that stayed current between report cycles, not a snapshot that went stale by the time it loaded. The bar was sub-second response on genuinely interactive visualizations, at a scale where naive client-side rendering or unoptimized queries would have made the dashboard unusable.
What we built
We built the dashboard on React for the UI shell, with custom D3.js charts instead of an off-the-shelf charting library, so we could control exactly how each visualization rendered at scale. A Node.js backend exposes a GraphQL API, letting the frontend pull only the fields a given view needs rather than over-fetching on data-dense screens. MongoDB holds the incoming financial data, modeled around the query patterns the dashboards actually run against. Live updates stream to the browser over WebSocket connections instead of polling, so charts update the moment new data lands rather than on a refresh cycle. AI-powered predictive insights run on top of that same pipeline, surfacing forward-looking signals alongside the historical view. AWS hosts the full stack, giving the ingestion and streaming layers headroom to scale as data volume grows.
How we approached it
Built custom D3.js chart components instead of adopting a general-purpose charting library, trading development time for the rendering control needed at 10M+ data points a day.
Used GraphQL instead of a REST API so each dashboard view fetches only the fields it needs, keeping payloads small on data-dense financial screens.
Put live updates on WebSocket streaming rather than polling, so new data reaches the charts the instant it occurs.
Layered AI-powered predictive insights on top of the same real-time data pipeline that feeds the live dashboard, so forecasts stay current with incoming data.
The impact
Data Points/Day
Report Speed
User Adoption
"The dashboard transformed how we make decisions. Worth every penny."
VP of Data
FinTech / analytics
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