Modern Real Estate Data
Case Study
Modernizing Real Estate Data Infrastructure for ATTOM
We partnered with ATTOM to modernize their real estate data infrastructure and overcome the limitations of legacy systems. Our objectives were clear: build a scalable, cloud-native platform for real-time data access, elevate data quality, and cut operational costs. Through the implementation of a dynamic data pipeline and a robust data quality framework, we significantly boosted data agility, speed, and reliability. This transformation not only enhanced operational efficiency but also reinforced ATTOM’s position as a leader in real estate intelligence.
The Vision
At ATTOM, we are building a cutting-edge, cloud-native platform designed to deliver real-time, high-quality real estate data at scale-faster, smarter, and more cost-efficiently than ever before. This next-generation foundation enhances data accuracy and agility, positioning us to lead the industry into an AI-powered future.
Scenario
Transforming Data Management
at ATTOM
ATTOM, a leader in property and neighborhood data, faced growing challenges with legacy systems that limited their ability to scale and serve clients effectively. Key issues included:
Slow ingestion and transformation cycles, delaying timely insights
Inconsistent data quality, impacting trust and decision-making
Limited scalability, restricting the onboarding of new data sources.
To overcome these obstacles, ATTOM set out to reimagine their data infrastructure. The mission: build a future-ready, cloud-native architecture capable of real-time insights.
What we did
Empowering Data Management with ATTOM: A Strategic Partnership
We’re proud to have partnered with ATTOM, a leader in property and neighborhood data, to design and implement a next-generation, cloud-native data platform on AWS. This transformation unlocked the full potential of ATTOM’s data assets-delivering real-time insights, improving data quality, and reducing operational overhead.
Using Amazon S3 and AWS Glue, we built a robust data lake that supports both raw and curated data zones. This architecture ensures efficient data storage, access, and analysis at scale. By integrating Kafka and Spark Streaming, we enabled real-time ingestion pipelines that process data as it arrives-empowering ATTOM with near-instant insights and faster decision-making.
Key features of the experience
The Impact
Driving Results with ATTOM: Real Impact, Real Innovation cultural legacy
Faster data processing
cutting data latency from hours to minutes and enabling real-time insights
Enhanced data accuracy
powered by a robust, rule-based quality engine.
Streamlined workflows
significantly reduced manual intervention and enhanced team productivity