About Client:
A global event management leader, the client orchestrates thousands of conferences, trade shows, and corporate events annually. Their business depends on understanding attendee behavior, optimizing on-ground experiences, and proving ROI to sponsors—making a reliable, scalable data foundation critical to operations.
As data volumes grew across digital touchpoints, the need for a modern Snowflake medallion architecture became central to supporting enterprise-wide analytics.
Background:
Rapid growth in digital engagement introduced multiple data sources, including ticketing systems, event apps, CRMs, and post-event surveys. The client’s legacy on-premise infrastructure struggled to integrate these streams efficiently.
Data silos and manual data preparation delayed insights, limiting real-time decision-making during live events. Without a structured medallion architecture Snowflake setup, analytics teams faced bottlenecks in delivering timely and trusted insights at scale.
Challenge:
The client faced several interconnected challenges:
- Siloed and inconsistent data across systems, eroding trust in reports
- Limited scalability, with infrastructure unable to handle event-driven data spikes
- Poor data quality due to flawed ingestion, leading to duplicates and errors
- Analytics bottlenecks, making real-time and predictive use cases impractical
- High manual overhead, as engineers spent excessive time fixing pipelines instead of enabling insights
These challenges highlighted the need for a modern event-driven architecture for Snowflake that could ingest, process, and serve data reliably during peak event activity.
