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CASE STUDY

Group Analytics Lakehouse

Real Estate & Property Development

Creation of a unified analytics platform consolidating multi-entity real estate data to support portfolio-level visibility and consistent performance reporting.

Large real estate groups operating across development, leasing, hospitality, and facilities management require consolidated visibility across subsidiaries and asset classes.

Operational systems such as ERP, CRM, and property platforms often operate independently, resulting in fragmented reporting and inconsistent KPI definitions.

A scalable analytics foundation must support portfolio-level visibility while preserving governance and access controls.

8+

Subsidiaries

70%

Faster Decisions

30+

Standard KPIs

Architectural Challenge

Multi-entity real estate groups commonly face:

  • Disparate data schemas across subsidiaries .
  • Manual reconciliation of financial and operational metrics .
  • Delayed reporting cycles.
  • Inconsistent KPI definitions.
  • Limited cross-portfolio visibility.

The central challenge is designing a governed data architecture capable of consolidating structured and semi-structured sources into a unified analytics platform..

Platform Architecture Approach

The lakehouse architecture incorporates:

Centralized ingestion pipelines from ERP, CRM, and operational systems

Schema validation and data quality enforcement layers

Scalable storage and compute layers for analytical workloads

Structured data modeling aligned to standardized KPI definitions

Role-based access control across business units

The design supports consolidated executive reporting as well as business-unit-level analytics consumption.

Operational Controls & Governance

To ensure sustainability and control, the platform includes:

  • Documented data models and lineage tracking .
  • Governance policies defining ownership and access rights .
  • Controlled onboarding processes for new subsidiaries .
  • Monitoring of ingestion pipelines and transformation logic .
  • Structured access provisioning aligned with enterprise security policies.

The architecture prioritizes long-term maintainability and portfolio expansion .

Platform Outcomes

The resulting data foundation enables:

  • Consolidated cross-portfolio visibility.
  • Consistent KPI definitions across subsidiaries.
  • Reduced reliance on manual reconciliation.
  • Scalable analytics expansion for new business units.
  • Structured governance embedded into reporting workflows.

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