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Data Warehousing for Investment Management: IBOR, Performance, and Research Data

Modern data warehousing for asset managers — Snowflake, Databricks, BigQuery, Fabric. Dimensional models for positions, transactions, performance, and risk with point-in-time correctness, IBOR reconciliation, and the GIPS-aware structure investment warehousing requires.

Why Investment Warehouses Don't Match the IBOR

An asset manager builds a data warehouse and the investment teams don't trust it. The reasons are familiar: positions in the warehouse don't quite match the IBOR because corporate actions were processed differently, performance numbers don't match GIPS composites because the methodology differs, and historical data has been restated in ways that make backtests show different results than they should. The warehouse is technically correct against the source extracts and functionally wrong against the official record. By month three, the research team is back to pulling data directly from the OMS and the operations team is reconciling manually.
Investment warehousing done right makes IBOR reconciliation and point-in-time correctness the foundations. Position and transaction data sourced from the IBOR after every cycle, with reconciliation that proves the warehouse matches. Corporate actions processed using the same methodology as the IBOR. Performance calculated using the GIPS methodology where composites apply. Bitemporal tables that preserve point-in-time accuracy for research. Master security data with vendor identifier mapping. With these foundations, the warehouse becomes the trusted source for trading, research, and reporting. Without them, it stays a parallel reality.

How Investment Firms Apply It

IBOR-Reconciled Position & Transaction

Position and transaction dimensional models reconciled to the IBOR — corporate action processing aligned, identifier mapping consistent, and the reconciliation jobs that prove the warehouse matches after every cycle.

Positions + transactions + IBOR + corp actions

Point-in-Time Research Data

Bitemporal data structures for research — backtests query data as it was known at the time, not as later restated. The foundation of research validity that prevents lookahead bias.

Point-in-time + bitemporal + backtest + lookahead

Performance & GIPS Composites

Performance calculation using the GIPS methodology where applicable — composite construction, return calculation, dispersion measurement. The structure that supports both internal performance reporting and external GIPS verification.

Performance + GIPS + composites + dispersion

What You Receive

Investment data warehouse delivered for trading, research, and reporting: position and transaction models reconciled to IBOR, point-in-time research data, performance and GIPS composites, master security data with identifier mapping, alternative data integration where applicable, and the documentation that supports investment team trust.

From Our Blog

Data Warehousing for Investment — FAQ

Snowflake, Databricks, BigQuery, or Fabric for investment warehousing?

Snowflake is most common at asset managers for its data sharing capabilities and ecosystem. Databricks wins for managers with significant quantitative research and ML workloads. Fabric for Microsoft-centric managers. The IBOR reconciliation and point-in-time discipline matter more than the platform choice.

Through encoding the GIPS methodology in the semantic layer — composite construction (which accounts in which composite), return calculation methodology, dispersion measurement, and the disclosures GIPS verification requires. We work with the GIPS team during implementation to ensure the methodology matches.

Yes. Pre-qualified data warehouse architects with investment management experience — IBOR reconciliation, point-in-time data, GIPS composites, performance attribution, and the dimensional modeling discipline investment warehouses require. 92% first-match acceptance.

A Warehouse the IBOR
Reconciles To

IBOR-aligned, point-in-time-correct, GIPS-aware — the warehouse trading, research, and reporting can trust.