NUCLEUS
Portfolio Demonstration Environment · Synthetic Data

NUCLEUS

Executive Analytics & Decision Intelligence Platform

An independently developed analytics platform by Shemal Dave, PhD, PMP — demonstrating end-to-end ownership across governed metrics, data modelling, executive BI UX, forecasting, anomaly detection, player analytics, experiment design and AI-assisted querying.

No sign-up · no password · read-only · fully synthetic dataset

Nucleus executive analytics portal — network performance dashboards
What it demonstrates

The full analytics stack, working

Every capability below is live in the demo — nothing is mocked in the UI. Click any dashboard and the numbers come from the same SQL metric layer.

Governed metric layer

Hold, RTP, rotation, net per store per day — each defined once in SQL. Dashboards and the AI read the same views, so there is exactly one version of every number.

Fourteen executive dashboards

Dense, boardroom-grade screens: CEO health, executive summary, trends, geography, leaderboards, game economics, player retention, promotion design.

Forecasting & anomaly detection

Holt-Winters forecasts with confidence bands per location, and a severity-ranked exception list of what broke out of band this week.

Player analytics

Cohort retention triangles, behavioural segments and churn-risk scoring over a synthetic player base.

Experiment design

An 18-run Taguchi array for promotion design — factor effects ranked by signal-to-noise, with a recommended configuration.

AI-assisted querying

Dr. D answers in plain English by writing read-only SQL against the governed views, with every question written to an audit log.

Global filters & theming

State, platform, product and period filters persist across every page; full dark/light theme support.

Security by construction

Row-level security, read-only query paths, server-mediated AI with the key never touching the browser.

How it's built

A governed metric layer, end to end

Frontend
React 19 · TanStack Start · Tailwind CSS v4 · Framer Motion
Data
Postgres star schema · row-level security · SQL views & RPC metric functions
Forecasting
Holt-Winters triple exponential smoothing with z-score severity bands
AI
Server-mediated assistant with prompt caching, governed SQL generation and audit logging
Hosting
Lovable Cloud (edge SSR + managed Postgres)
About the builder

Designed & built by Shemal Dave

Nucleus is an analytics platform I designed and built end-to-end as a portfolio project: the warehouse schema, the governed SQL metric layer, the forecasting engine, the executive UI, and the AI assistant that reads the same views the dashboards do.

The dataset is fully synthetic — a simulated distributed route gaming network — but every screen behaves the way a production deployment would, because every number is computed in SQL, never in the browser.

  • PhD — applied research in statistical modelling and decision systems.
  • PMP-certified program leadership across data platform builds.
  • Nucleus is an independently developed portfolio build — designed and implemented from scratch to demonstrate analytics architecture, executive BI, statistical modelling, metric governance and AI orchestration skills.
Portfolio Demonstration Environment · Synthetic Data

See it working — one click, no sign-up

NUCLEUS

Executive Analytics & Decision Intelligence Platform. Designed & built by Shemal Dave, PhD, PMP as a portfolio demonstration environment — every figure is synthetic data.

Demo
Builder
© 2026 Shemal Dave · Nucleus is a personal portfolio projectPortfolio Demonstration Environment · Synthetic Data