Query-ready
Connect Power BI, Tableau, or any OLAP tool to conformed star schemas, no raw-table wrangling.
BI & OLAP Marts module
A ready-to-BI warehouse over your trading data
Gravitas builds a governed, star-schema analytical layer directly over the trading model , conformed dimensions and purpose-built marts for trade, position, hedge, P&L, physical operations, options Greeks, and back office, so your BI tool connects to trusted, query-ready data instead of raw tables.
Overview
From transactional model to analytics, governed end to end
Operational trading data is normalized for correctness, not for analytics. The Gravitas BI & OLAP layer transforms it into dimensional star schemas, conformed dimensions plus fact marts, that BI and OLAP tools query directly. Every mart is built from the same governed source that carries a trade from capture to cash, so position, P&L, and risk analytics reconcile with the front and back office by construction.
Reference and market data are managed as slowly-changing dimensions (SCD Type 2), so analytics are correct as-of any date. Fact marts are incrementally refreshed and fully lineage-tracked, giving analysts a trusted semantic layer rather than a nightly export that has to be reconciled before anyone trusts a number.
Workflow
How it works on the desk
01
Model
Conformed dimensions from reference and market data, as-of correct (SCD Type 2).
02
Build
Fact marts, trade, position, hedge, P&L, physical ops, Greeks, cashflow, as star schemas.
03
Refresh
Incremental, lineage-tracked loads keep marts current against the governed model.
04
Serve
A governed semantic layer any BI or OLAP tool connects to directly.
Feature matrix
Capabilities at a glance
| Mart / layer | Grain | Key measures & content |
|---|---|---|
| Reference & Market-Data Dimensions | Conformed dim (SCD2) | Instrument, commodity, book, counterparty, calendar, curve, FX, and location, versioned as-of date |
| Trade + Leg Mart | Trade / trade-leg | Economic terms, quantities, prices, buy/sell, per-leg breakdown for multi-leg structures |
| Position & Price Mart | Position by book & tenor | Net & gross position, average price, delta-equivalent, physical and financial |
| Hedge Mart | Hedge relationship | Hedge & hedged item linkage, hedge ratio, effectiveness, financial and physical |
| P&L, Inception | Trade | Day-1 / inception P&L at trade date |
| P&L Explained | Position / risk factor | P&L attribution by factor, price, curve, time, FX, new trades, amendments |
| Physical Ops Mart | Nomination / delivery | Nominations, scheduled vs. actual, balance details, imbalance |
| Options Greeks Mart | Option position | Delta, gamma, vega, theta, rho and cross-gamma / cross-greeks |
| Back-Office / Cashflow Mart | Cashflow / settlement | Projected & actual cashflows, invoice linkage, settlement status |
| Risk & VaR / Exposure Mart | Book / portfolio | VaR, sensitivities, limit utilization, scenario & stress results |
| Credit & Counterparty Mart | Counterparty | Credit exposure, CVA inputs, limit utilization by counterparty |
| Regulatory / Compliance Mart | Reportable event | EMIR / Dodd-Frank / position-limit reporting datasets |
| Audit & Lineage Mart | Record version | Source-to-mart lineage, load audit, as-of reconstruction |
Who it’s for
Built around the roles that use it
BI & analytics teams
Quant & risk
Trusted factors
P&L-explained and Greeks marts share the same positions risk runs on, so attribution ties out.
Finance & back office
Reconciled by design
Cashflow and settlement marts trace to the same trades the front office booked.
FAQ
Questions
What exactly is delivered, a database or a tool?
A governed, BI-ready data layer: conformed dimensions and star-schema fact marts materialized over the trading model, which any BI or OLAP tool connects to. It is a semantic warehouse, not another dashboard product.
Which marts are included?
Reference & market-data dimensions; Trade + leg; Position & price; Hedge (financial and physical); P&L inception and P&L explained; Physical Ops (nomination / balance); Options Greeks (including cross-gamma); Back-office cashflow; plus risk/VaR, credit, regulatory, and audit/lineage marts.
How is as-of correctness handled?
Reference and market data are modeled as slowly-changing dimensions (SCD Type 2), so any mart can be queried as-of a chosen date and analytics remain historically accurate.
Do the marts reconcile with the front and back office?
Yes. Every mart is built from the same governed model that carries a trade from capture to cash, and each is lineage-tracked, so position, P&L, risk, and settlement analytics tie out by construction rather than by nightly reconciliation.
How are the marts refreshed?
Through incremental, lineage-tracked loads that keep them current against the governed model, rather than full nightly rebuilds.
See it on your trades
Request a demo of BI & OLAP Marts
A working walkthrough of BI & OLAP Marts mapped to your commodities and workflows.