Enhancing Data Governance for a Real Estate Giant

About Client:

Our client, a billion-dollar home leasing company, dominates the real estate market with over 100,000 rental homes scattered across the United States.


Operating as a multi-billion B2B leasing enterprise with ambitions for continuous growth, our client faced a daunting challenge in managing their data.The need to centralize data governance arose from the significant challenge of updating data from multiple sources. Given the critical importance of data governance in ensuring data quality, security, and compliance, our client sought a solution to modernize their data architecture. They approached us with the goal of ingesting data from SQL to Snowflake, aiming for robust data governance practices that could handle complex analytical tasks, streamline operations, and facilitate efficient data ingestion.


  1. Inconsistent Data Quality: An absence of standardized data quality procedures led to inaccuracies in analyses and decision-making processes.
  2. Lack of Data Governance Framework: The absence of a robust data governance framework resulted in data disorganization, security vulnerabilities, and integration challenges.
  3. Complex Data Integration: Managing data from nine different sources, with plans for future expansion, required a scalable and adaptable data architecture. The absence of such architecture hindered the client’s ability to obtain accurate reports for informed decision-making.

Our Solution:

To address these challenges, we implemented a comprehensive data governance strategy:

  1. Seamless Data Transfer: We orchestrated a smooth transition of data from SQL to Snowflake, employing pipelines that preserved data integrity and adhered to established quality standards.
  2. Establishing Data Policies: From the ground up, we crafted essential data policies, including data dictionaries, catalogs, and lineage tracking, ensuring data security, enhanced comprehension, and seamless integration.
  3. Comprehensive Data Quality Framework: We deployed a robust data quality framework encompassing various checks like duplicate detection, range verification, and data profiling to ensure data consistency.
  4. Future-Proof Architecture: Recognizing the client’s data integration plans, we designed an architecture capable of accommodating initial data sources with provisions for further expansion.


  1. Centralized Data Repository: Ingestion to Snowflake EDW provided a centralized repository, simplifying access and analysis for decision-makers.
  2. Effort Reduction: Improved data management resulted in a 30-35% reduction in efforts required for building data ingestion pipelines.
  3. Enhanced Data Transparency and Security: Established data governance policies empowered data-driven decision-making and investment strategies by ensuring transparency, quality, and security.
  4. Compliance Adherence: Data governance policies mitigated compliance risks, ensuring adherence to industry regulations.
  5. Facilitated Business Growth: The scalable data architecture enabled business growth and innovation, setting the stage for future success.

By implementing robust data governance practices and modernizing their data architecture, our client gained actionable insights, minimized risks, and positioned themselves for sustainable growth in the competitive real estate market.

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