A Broadcasting & Digital Advertising Platform Delivered AI-Powered Reporting with Snowflake

Customer Background

A broadcasting and digital advertising organization manages large-scale campaign data across broadcast, digital, and performance channels. The platform processes massive volumes of impression and click-through data, enabling marketing and media teams to evaluate campaign effectiveness and optimize spend.

With over 24 TB of historical advertising data, the organization needed faster access to insights, near-real-time reporting, and a self-serve analytics experience for business users. To eliminate manual reporting bottlenecks and enable AI-driven decision-making at scale, the company partnered with Sigma Solve to modernize its analytics foundation using Snowflake and Generative AI.

Industry

Logistics

Challenges

The organization struggled to extract timely and actionable insights from a rapidly growing analytics environment, impacting campaign optimization and decision speed.

  • Large-Scale Data Performance Constraints
    Querying and analyzing 24 TB of historical advertising data resulted in slow response times and delayed insights.
  • Manual, Analyst-Dependent Reporting
    Analysts relied on manual reporting workflows, making it difficult to monitor impressions and click-through rates in near real time.
  • Lack of Self-Service Analytics
    Business and marketing teams depended heavily on analysts for ad-hoc questions, creating bottlenecks and slowing decision-making.
  • Limited Real-Time Visibility
    Campaign performance insights lagged behind execution, reducing the ability to react quickly to trends and anomalies.

The Solution

Sigma Solve designed and implemented a Snowflake-powered, AI-driven reporting platform optimized for performance, scalability, and self-service analytics.

  • Migrated analytics workloads to Snowflake, enabling elastic, high-performance data processing at scale.
  • Implemented live data ingestion pipelines using Airbyte, ensuring near-real-time availability of advertising data.
  • Enabled natural-language analytics using LangChain, translating business questions into SQL queries powered by GPT-4o Mini.
  • Developed an interactive Vue 3 single-page application featuring dashboards, account-level analytics, and CSV/PDF exports.
  • Optimized performance through hot-query caching and serverless workflows, delivering consistent sub-second query execution.
  • Designed the platform for self-service access, reducing dependency on analyst-driven reporting.

The Outcome

Sigma Solve’s AI-powered Snowflake implementation transformed how advertising teams accessed and acted on data. The company got faster insights across 24 TB of historical advertising data, real-time visibility into campaign performance, reduced reporting bottlenecks and analyst workload and data-driven optimization across broadcast & digital advertising efforts.

Common analytics queries now deliver sub-second performance.

Campaign metrics such as impressions and CTRs are available in near real time.

Marketing and business teams gained self-serve analytics, significantly reducing reliance on analysts.

Decision-making accelerated across campaigns, accounts, and channels.

The platform scaled effortlessly with growing data volumes and reporting demand.

Client Testimonial

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