Flagship Independent Build
Executive Analytics & Decision Intelligence Platform
Most analytics estates fail the same way. Numbers live in fragmented reports, KPI definitions drift between teams, executives wait days for an analyst to run something, and forecasting or AI work sits disconnected from the governed data underneath. Nucleus is my answer to that problem, designed and built independently end to end.
One platform, owned end to end.
I designed and built Nucleus myself: the data architecture, the governed metric layer, the executive portal UX, the statistical engines, the access-control model, and the AI answer layer that sits on top of all of it.
The organising idea is a single governed metric layer. Formulas such as hold, RTP, rotation and net/store/day are defined centrally in SQL and governed views. Every consumer — a dashboard, a forecast, an anomaly score, or an AI answer — resolves the same definition. Nothing gets to invent its own version of a KPI.
On top of that layer, Nucleus adds boardroom-grade executive screens, Holt-Winters forecasting with confidence bands, severity-ranked anomaly detection, cohort and segmentation analytics, Taguchi-style experimental design for promotions, and a natural-language query layer restricted to read-only governed tools.
Data flow, with governance as a cross-cutting layer.
Operational & transactional data
Scheduled, idempotent ingestion
Star schema · governed views
Boardroom-grade screens
Read-only governed queries
Governance & security — applies to every layer above
Six layers that share one definition of the truth.
01
A dense, boardroom-grade portal rather than a scattering of one-off reports. Every screen answers a question an executive actually asks in a review.
02
Forecasts and anomaly detection sit on the same governed numbers as the dashboards, so a projection and a report never disagree.
03
Behaviour analysis built as a reusable layer instead of an ad-hoc extract, so cohort and value questions are answerable on demand.
04
Promotion and configuration decisions are treated as experiments with a designed matrix, not as opinion contests.
05
Natural-language questions are translated into constrained, read-only queries and tools against the same governed layer — auditable answers, not free-form number generation.
06
Access and traceability designed in from the start, because an executive platform is only trusted if it is controlled.
The four choices that make the rest of it hold up.
Hold, RTP, rotation and net/store/day are defined once in SQL and governed views. Dashboards, forecasts and the AI layer all read the same definition, so KPI drift between a deck, a report and a chatbot answer becomes structurally impossible instead of a review-meeting argument.
Full refreshes get slower and more fragile as history grows. Incremental, scheduled ingestion keeps load windows predictable, makes reruns safe, and keeps the executive portal current without a fragile overnight monolith.
Per-dashboard extracts fork the truth. A star schema with governed views on top gives one modelling surface, so adding a screen or a statistical engine is a read against existing dimensions rather than a new pipeline.
An LLM given open database access is both a correctness risk and a security risk. Constraining it to governed, read-only tools means answers are reproducible, permissions still apply, and every number can be traced back to a definition.
For hiring managers: the scope a BI or analytics leader is actually being asked to own.
Designed the path from source systems through incremental loads into a star schema with governed views — and kept the metric layer as the contract.
Holt-Winters forecasting, anomaly severity scoring, cohort retention and Taguchi-style designed experiments implemented as engines, not one-off analyses.
Scoped screens around the decisions executives actually make, and sequenced the build so each layer made the next one cheaper.
Dense boardroom-grade views that lead with the answer, with drill-through available for anyone who wants the working.
An answer layer built on governed tools and read-only query paths, so natural-language access is auditable rather than speculative.
Data modelling, statistical engines, front-end UX, access control and AI integration — designed and built as one coherent platform.
For recruiters & hiring managers
A fully interactive environment seeded with synthetic data and strictly read-only — safe to explore the governed metrics, forecasts, and AI query layer without touching anything real.