Real Estate Project

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Project overview

Real estate data platform utilizing Python for automation and Looker Studio for managing high-performance brokerage visualizations integrated with PostgreSQL.

A high-performance brokerage dashboard!

The challenge of project

Building a responsive Looker Studio dashboard capable of supporting over 6,000 real estate agents.

Developing automated Python pipelines to sync listing data from diverse cloud sources into PostgreSQL.

Calculating complex GCI (Gross Commission Income) metrics in real-time.

Key Metrics

  • GCI Tracking: Monitoring multi-million dollar commission flows across thousands of agents.
  • Data Sync Speed: Reducing daily synchronization time by 60% using asynchronous Python tasks.

Solutions

A microservices-based approach with Python for data processing and Looker Studio for a clean, interactive interface for agents to track their performance.

Benefits

  • Looker Studio Visuals: Interactive and real-time visualization of Referral Income and GCI across the entire brokerage.
  • Streamlined Workflows: Automated listing updates reducing manual data entry for administrative staff.
  • Personalized Access: Secure, individual agent logins providing clear visibility into personal sales pipelines.
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