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Real-Time and Batch Data Ingestion Using Snowflake OpenFlow for a Healthcare Analytics Platform 

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    Executive Summary

    A leading healthcare organization managing 15 heterogeneous SQL Server source systems needed to consolidate data into a unified Snowflake-based analytics platform while supporting both CDC/incremental ingestion and daily full loads. 

    Anblicks designed and implemented a dual-pattern ingestion architecture using Snowflake native OpenFlow for both CDC and Non-CDC data movement. The framework supports 350+ tables and automated downstream processing through Snowflake Tasks. 

    The solution reduced source-data ingestion time from 6–8 hours to 20 minutes–2 hours, delivering approximately 60% efficiency improvement while enabling daily-fresh data and consistent execution across all 15 source systems. 

    The Breakthrough
    • Reduced from 6–8 hours to 20 minutes–2 hours source-data ingestion time. 
    • ~60% efficiency improvement from the modernized ingestion approach.  
    • 15 source systems running in parallel within the daily scheduling window.  
    • 350+ tables supported through the scalable ingestion framework. 
    • 300+ Snowflake Tasks automate CDC change consumption and downstream processing.  
    • Daily-fresh, near real-time data availability for BI, reporting, and clinical teams, with zero-data-loss ingestion through CDC streams.  
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