Introduction

For a large manufacturing company with billions of equipment assets and parts. Manages assets through application hosted on Azure. Generating servicing schedules and asset details. Is creating lot of performance bottle-necks and not scalable.

• Complex SQL data flows need to be simplified with better data architecture

• Scalability should be dynamic with out infra team involvement

• In efficiencies in data processing need to be eliminated 

• Bringing data from different sources and integrating with other snowflake systems.

• Building hierarchical security model so that assets can be managed at different levels of the organization

• Designed and implemented a scalable, cloud-native Snowflake architecture, optimizing SQL-based data flows.

• Standardized data storage and governance, ensuring seamless integration with the existing Snowflake ecosystem.

• Improved scalability and system efficiency by consolidating infrastructure within Snowflake's elastic computing environment.

• Designed an optimized data pipeline to process millions of records from connected devices in real-time.

• Scalability & Performance: Manages billions of records from connected devices seamlessly. Technological Framework

Why these technologies?

Snowflake's elastic compute separates storage from processing, enabling dynamic scaling of asset servicing workloads without infrastructure team involvement — eliminating performance bottlenecks during peak processing periods.

Why this Setup?

Multi-state pipelines with Snowflake stored procedures and tasks enable complex, hierarchical asset data to be transformed and enriched in real-time — generating accurate servicing schedules for billions of equipment records.

Why this Setup?

Seamless integration with the existing Snowflake ecosystem and Azure-hosted application ensures zero disruption to ongoing operations, while connected device data streams enable near real-time servicing schedule accuracy.

Takeaway

Zapcom unified a large manufacturer's asset management onto a scalable Snowflake architecture — achieving 22% optimised workflows and 28% improvement in near real-time scheduling accuracy for billions of equipment records.