Accelerating AI Insights: Snowflake-Powered Content Analysis

Client provides third-party content-level contextual analysis and brand safety solutions to publishers, DSPs, agencies and advertisers.

Challenges

  • Current system unable to cope with growing data size (in TBs) and not extensible due to flat structure​
  • Insights could be generated for limited number of days and any extended period resulted in system timeouts​
  • Generating new insights was complex and time consuming

Solution

  • Snowflake data warehousing enabled generating analytical insights at scale.​
  • Transitioned from Athena to Snowflake, utilized  Snowflake to deliver new MVPs, while migrating the rest in parallel.​
  • Leveraged curated data tables to optimize time-to-market by ensuring data readiness.​
  • Curtailed learning curve by reusing Apache Airflow to sync data between S3 and Snowflake.​
  • Tech Stack: ​
    • Pipelines: Apache Spark, Apache Airflow, AWS (Athena,S3, Redis, ECS) ​
    • Reporting: Google Looker, Docker​
    • API: Python

Impact Generated

  • 86% Boost New explore (Snowflake): < 8 seconds as compared to old explore (Athena Query): > 60 seconds​​
  • Scalable ​Transitioning from Athena to Snowflake enabled generating insights for a larger date range that previously resulted in timeouts with Athena​​
  • Extensible Curated tables enabling versatile usage across dimensions, supporting internal and customer-facing insights​
  • Seamless transition Ensured seamless transition with minimal disruption to ongoing operations​

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