Snowflake Data Migration with Informatica IDMC Solutions - LTM

Client

A global property services provider with a diverse portfolio across residential and commercial markets. Operating in competitive, regulation-heavy environments, the company relies on trusted data to drive faster decision-making, maintain compliance, and ensure transparency across operations. For this initiative, the client aimed to modernize its data infrastructure to unlock the full potential of analytics and AI while future-proofing operations against market disruption.

Market Trends in Real-Estate

The real estate sector is undergoing rapid digital transformation, fueled by the need for real-time insights, seamless client experiences, and operational efficiency. In both residential and commercial markets, agencies are accelerating cloud adoption to unify fragmented data sources, enable advanced analytics, and scale AI-driven decision-making.

Heightened regulatory requirements are pushing organizations to strengthen compliance, data governance, and transparency. At the same time, competitive pressures demand faster deal cycles and agile operations. Leading real estate enterprises are investing in modern, cloud-based data ecosystems to eliminate legacy limitations, improve interoperability, and deliver trusted insights at speed and scale.

Need for Change

Operating in fast-moving, regulation-driven markets, the client faced mounting pressure to modernize its legacy on-premises data infrastructure. Its existing systems could not deliver the agility, transparency, and scalability needed to support advanced analytics and AI adoption. Key challenges included:

• Fragmented and inflexible legacy warehouse: The on-premises SQL Server environment struggled to integrate disparate data sources across hybrid setups, limiting interoperability and slowing innovation.
• Lack of real-time ingestion capabilities: Data pipelines could not support immediate availability, delaying insights and reducing responsiveness in decision-making.
• Manual, resource-intensive processes: Heavy reliance on manual integration and validation slowed project delivery and diverted resources from strategic priorities.
• Limited transparency and traceability in pipelines: The absence of end-to-end observability created blind spots, increasing operational risk and impacting compliance readiness.
• Scalability constraints for advanced analytics and AI: Existing infrastructure could not handle the performance demands of modern analytics, limiting the client’s ability to innovate and compete effectively.

LTM Solution

To address these challenges, LTM partnered with the client to execute a comprehensive data warehouse modernization program. The approach combined strategic planning, seamless execution, and risk mitigation to ensure a disruption-free migration while enabling a secure, agile, and future-ready data environment. Key interventions included:

• Assessed legacy environment and defined migration roadmap

Conducted a detailed review of the existing SQL Server setup, identified operational risks, and developed phased migration and risk mitigation plans.

• Migrated to Snowflake using Informatica IDMC pipelines

Used Cloud Data Integration and Cloud Mass Ingestion to ensure seamless data transfer from on-premises to Snowflake.

• Implemented automated testing with IDMC Data Validator

Eliminated manual validation bottlenecks by automating data quality checks, ensuring accuracy and consistency post-migration.

• Ensured zero business disruption during migration

Designed and executed a smooth transition plan to maintain operational continuity while modernizing the data environment.

• Established a future-ready data architecture

Delivered a secure, scalable, and cloud-native data platform to support advanced analytics, AI adoption, and continuous innovation.

Business benefits

• 10x faster data ingestion throughput

Reduced time-to-insight significantly, enabling quicker and more informed business decision-making.

• 5-star transparency rating

Achieved complete observability and traceability across data pipelines, strengthening compliance monitoring and stakeholder trust.

• 80% reduction in manual intervention

Automated data validation and integration processes freed up resources for higher-value strategic initiatives.