About the Client:
A leading commercial real estate firm with a robust portfolio of office, retail, and industrial properties across major metros. Their operations are data-intensive, relying on rich datasets like acquisition pipelines, leasing terms, tenant data, financial KPIs, and valuation models.
Background:
The client had recently migrated their analytics and operational workloads to Snowflake, consolidating fragmented systems and dramatically improving query speed. Teams relied on real-time and frequently updated datasets, but the high data velocity introduced issues around data integrity, rollback, and historical analysis. The absence of efficient historical data access posed barriers to agility and compliance.
Challenge:
The client faced recurring issues that limited their ability to recover and analyze data effectively:
- Accidental data overwrites or deletions caused by multiple users and automated pipelines
- Inability to easily answer questions like “What did this dataset look like last Tuesday?”
- Manual and inefficient rollback processes for erroneous loads or transformations
- Difficulty testing “what-if” scenarios without risking live data
- Gaps in maintaining immutable historical records for audits and regulatory compliance
