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Property Management Data Platform

Created a unified data platform for a commercial real estate firm managing $5B in assets, enabling data-driven investment decisions.

Key Results

45+
Data Sources Unified
90% faster
Report Generation
Days to hours
Portfolio Analysis Time
99.2%
Data Quality Score

The Challenge

A commercial real estate investment firm managing 200+ properties worth $5B in assets was drowning in data silos. Property performance data, market analytics, tenant information, and financial metrics lived in dozens of disconnected systems, making portfolio-level analysis nearly impossible.

Key Pain Points

  • 45+ data sources with no unified view of portfolio performance
  • Monthly reporting taking 2 weeks to compile manually
  • Investment decisions based on outdated data (30-60 days old)
  • No ability to perform scenario modeling across the portfolio

Our Approach

We built a modern data platform that unified all property data sources and enabled real-time portfolio analytics and investment modeling.

Phase 1: Data Integration

  • Cataloged and prioritized all 45+ data sources
  • Built automated ingestion pipelines for property management systems
  • Integrated market data feeds (CoStar, REIS, census data)
  • Created standardized data models for properties, leases, and financials

Phase 2: Analytics Layer

  • Developed a property performance scoring model
  • Built market comparison analytics with peer benchmarking
  • Created cash flow projection models with sensitivity analysis
  • Implemented automated anomaly detection for occupancy and rent trends

Phase 3: Self-Service Platform

  • Deployed a data warehouse with semantic layer for business users
  • Built executive dashboards for portfolio-level KPIs
  • Created deal analysis tools for acquisitions team
  • Implemented data quality monitoring and alerting

Technical Implementation

Architecture Highlights

  • Ingestion: Airbyte for connectors, custom APIs for legacy systems
  • Storage: Snowflake data warehouse with time-travel capabilities
  • Transformation: dbt for data modeling with full lineage
  • Analytics: Looker for dashboards, Python notebooks for analysis
  • Orchestration: Dagster for pipeline management and monitoring

Data Governance

  • Implemented data classification and sensitivity tagging
  • Created access controls aligned with role-based permissions
  • Built audit logging for compliance and investor reporting
  • Established data quality SLAs with automated monitoring

Results

The platform launched in 8 months, immediately transforming how the firm operates:

  • 45+ data sources unified into a single source of truth
  • 90% reduction in time spent generating monthly reports
  • Days to hours for portfolio-wide analysis that previously took weeks
  • 99.2% data quality score with automated validation and monitoring

Client Testimonial

"We went from making decisions based on gut feeling and outdated spreadsheets to having real-time visibility across our entire portfolio. It's completely changed how we evaluate investments."

— Chief Investment Officer

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