Helping more people find their next dream home
Housing.comDelta Lake · Unity Catalog · MLflow +2Housing.com, a real estate platform, moved from a cloud data warehouse to the Databricks Data + AI Platform, using Delta Lake and MLflow to train and deploy machine learning models for personalized property recommendations and fraud detection; additional ML models for pricing prediction and demand forecasting are currently under development. The fraud detection ML model lowered fraudulent credit card transactions by 0.05%, the recommendation engine drove a 5.5% increase in prospect-to-lead conversion, and the company cut total cost of ownership by 50% while reducing ML and pipeline deployment time by 10-15%.
Overview
Housing.com, a real estate platform, moved from a cloud data warehouse to the Databricks Data + AI Platform, using Delta Lake and MLflow to train and deploy machine learning models for personalized property recommendations and fraud detection; additional ML models for pricing prediction and demand forecasting are currently under development. The fraud detection ML model lowered fraudulent credit card transactions by 0.05%, the recommendation engine drove a 5.5% increase in prospect-to-lead conversion, and the company cut total cost of ownership by 50% while reducing ML and pipeline deployment time by 10-15%.
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Inspect the highlighted sourceThe challenge
Data silos across teams threatened accuracy, and Housing.com struggled with pricing accuracy, demand forecasting, personalization and fraud detection as data volumes scaled; moving away from a cloud data warehouse, the cost of computing was proving far more expensive than storage.
The solution
Housing.com moved from its cloud data warehouse to the Databricks Data + AI Platform (paired with AWS), using Delta Lake as the foundational storage layer, MLflow to train and deploy ML models, Unity Catalog for governance, and Tableau for BI/reporting, to power a property recommendation engine and fraud detection; ML models for pricing prediction and demand forecasting are still under development.
Reported business value
Housing.com cut total cost of ownership by 50%, reduced pipeline/ML deployment time by 10-15% (saving one week of manual ML deployment work), increased team productivity/collaboration speed by 20%, lowered fraudulent credit card transactions by 0.05%, and increased the prospect-to-lead conversion rate by 5.5% via the recommendation engine.
Sources
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