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Trusted property data. Better financial decisions.

· 6 min read
Calum Miller
Calum Miller
Director

A governed analytical foundation for property fund administrators, investment managers and financial reporting teams.

Property management platforms are essential operational systems. Yet fund accounts, investor statements and portfolio analysis often depend on data scattered across property ledgers, banking platforms, valuation files and manually maintained spreadsheets. Millersoft Data Vault Engine & Studio brings these sources together without replacing the systems teams rely on.

Talk to our teamExplore the pain points
Infographic: trusted data for property portfolio decision making. The Millersoft Data Vault Engine & Studio creates an analytical foundation for property data, combining Yardi and other systems to deliver accurate, timely and trusted reporting, with portfolio performance, income and cash flow, regulatory reporting and property analytics. Common reporting challenges: siloed data, slow reporting, inconsistent figures, audit and regulatory pressure, and limited analysis. Data from Yardi (property and asset management), finance systems (general ledger and fund accounting), other sources (valuations, ESG, market data, CRM) and external data (economic, planning and location data) flows through ingestion and change capture into the Millersoft Data Vault Engine & Studio, which models hubs (business entities), links (relationships) and satellites (historical changes) with auditable history, source lineage and repeatable transformations. Business rules and analytical data models then serve financial reporting, portfolio analytics, investor reporting and Excel / Sheetloom. Key benefits: complete visibility, greater accuracy, faster reporting, audit ready and better decisions. (opens the full-size image in a new tab)

When reporting becomes a reconciliation exercise​

Financial reporting teams need to explain not only what a portfolio is worth today, but how balances, valuations and ownership structures changed. Disconnected systems can make that explanation expensive, slow and difficult to reproduce.

The reporting pain points that matter​

Property ledger to fund accounts
Property-level income, expenses, accruals and cash movements may not reconcile cleanly to fund or SPV general ledgers. A warehouse can match source transactions, retain adjustments and surface unexplained differences.
NAV and valuation history
Appraisals, capex assumptions, FX rates and ownership interests change over time. Versioned data enables controlled comparisons between reporting dates and explanations of NAV movements.
Intercompany and multi-entity
Property holding structures span SPVs, funds and jurisdictions. A common model maps entities, ownership, currencies and consolidation rules while retaining the original records.
Rent roll and lease exposure
Lease amendments, incentives, arrears, expiries and vacancies affect forecasts. Historical snapshots support tenant concentration, WAULT, occupancy and rental growth analysis.
Cash flow and liquidity
Bank balances, rent receipts, debt service, capital calls and planned capex sit in different places. Combining them supports fund-level liquidity forecasts and variance analysis.
Investor and regulatory packs
Different clients, funds and jurisdictions demand different reporting formats. Governed datasets allow repeatable packs with traceable figures, subject to appropriate reporting controls.
Audit and restatements
Late journals and corrected source records can alter previously published numbers. Effective-dated history and publication snapshots help reconstruct what was reported and why it changed.
ESG and property metrics
Energy use, emissions, floor area and building attributes often live outside finance. Linking these datasets to properties and reporting periods supports more consistent disclosures.

What makes the warehouse valuable​

The value is not another dashboard. It is a dependable layer of integrated, historical data beneath fund accounts, investor reporting and investment analysis. Business rules remain explicit, source records remain traceable and downstream reports can use the same governed definitions.

From fragmented systems to portfolio intelligence​

Infographic: turn property data into trusted insight. For financial service firms managing client property portfolios, the Millersoft Data Vault Engine & Studio provides the analytical foundation to integrate Yardi and other systems, preserve the full history of data and support accurate, auditable and insightful reporting. The challenge: multiple data sources, data quality and consistency, historical reporting, regulatory demands and client transparency. How a data warehouse helps: a single governed data model, complete history, audit and compliance, flexible reporting, and a foundation ready for AI and advanced analytics. Data from Yardi (property management), accounting and finance, valuations and appraisals, banking and transactions, and other sources (ESG, CRM and more) flows through the Millersoft Data Vault Engine & Studio (hubs for key business entities, links for relationships, satellites for historical changes, with auditable history, source lineage and repeatable transformations) to client reporting, regulatory reporting, management dashboards and Excel / Sheetloom. Key reporting use cases: portfolio performance, investor and client reporting, regulatory compliance (AIFMD, CSSF, FATCA, CRS and other requirements), ESG and sustainability, and property and tenant analysis. (opens the full-size image in a new tab)

How the Engine & Studio works​

The Engine ingests permitted data from Yardi and complementary sources such as fund accounting systems, banks, valuation providers and document-derived datasets. Studio supports the design and maintenance of Data Vault models built around properties, leases, tenants, funds, legal entities and transactions.

Hubs preserve business identities, links preserve relationships and satellites retain descriptive changes with appropriate source and load timestamps. Curated business views then apply approved accounting, valuation and consolidation logic for reports and dashboards.

Integration method, extraction frequency and change capture depend on the customer’s licensed interfaces, deployment arrangements and available source history. A warehouse cannot recreate changes that were never captured.

A practical first engagement​

Start with one high-value reporting problem​

A strong initial demonstration is a quarter-end property-to-fund reconciliation. Select one fund, several properties and a reporting period. Compare property income and expenses with the fund ledger, identify timing differences and journal adjustments, then reconstruct the figures used in the original investor pack.

Illustrative delivery sequence​

  • Discovery: agree reporting definitions, source access, control requirements and the financial questions to answer.
  • Pilot: ingest representative source data, model key business entities and demonstrate reconciliation with lineage.
  • Expansion: extend to historical NAV, cash flow, investor reporting and multi-entity analytics after the pilot proves value.

The outcomes to measure​

Measure time spent assembling monthly or quarterly packs, the number of unresolved reconciliation breaks, time required to answer an auditor’s query and the effort needed to reproduce a previously published figure. Establish a baseline before claiming improvement.

Designed to complement existing reporting tools​

The warehouse can feed existing BI applications, controlled Excel models and Sheetloom-produced reporting packs. Finance teams keep familiar outputs while benefiting from a more consistent analytical foundation.

Make every number explainable

Talk to Millersoft about building a trusted analytical foundation for your property portfolios. Start with the reporting issue consuming the most time and prove the value with your own data.

Discuss your property reporting challenge

Yardi is a trademark of Yardi Systems, Inc. Millersoft is not affiliated with Yardi Systems, Inc.