Automation Platform

Real Estate Data Automation & Reporting

An automation system for collecting, enriching, and reporting high-value property market data.

2024Automation Platform

Type

Automation

Focus

Data reliability

Outcome

Faster reporting

Project overview

Business problem and implementation scope

Engineered a Python-based scraping and reporting workflow that transformed scattered property data into structured business intelligence for ongoing decision-making.

Problem: The business relied on slow, repetitive manual data collection from multiple real estate sources, which created accuracy issues and delayed reporting.

Role: Owned scraping architecture, pipeline reliability, normalization logic, storage design, and downstream reporting interfaces.

Tech stack

PythonDjangoPostgreSQLCeleryRedisDockerAWS

Project schema value

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Features

  • Automated collection from multiple real estate data sources
  • Normalization and validation workflow for structured analysis
  • Scheduled background jobs and failure monitoring
  • Reporting interface for analysts and business teams

Challenges solved

  • Making scrapers resilient to source changes and anti-bot friction
  • Cleaning inconsistent source data into a usable schema
  • Ensuring recurring jobs remained observable and maintainable

Business value

  • Reduced manual research workload significantly
  • Improved reporting consistency and turnaround time
  • Created a repeatable data asset for decision-making
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