How Luminate Uses Snowflake to Deliver Billboard Chart Data 334% Faster
Luminate is the entertainment industry’s premier data partner, powering the Billboard charts and delivering insights to major record labels, studios, and talent agencies across music, film, and television. The company migrated from on-premises infrastructure to Snowflake to unify 3.5+ terabytes of daily data ingestion and enable cross-industry analytics at scale. Daily processing speed improved by 334% and customer data delivery dropped from several days to minutes.
Impact
334%
Daily processing speed increase
3.5+ terabytes
Daily data processed
1 trillion+
Data points processed daily
Minutes (vs. several days)
Customer data delivery time
Challenge
Luminate’s on-premises Spark and SQL Server infrastructure could not process 3.5+ terabytes of daily data efficiently—end-of-month market reports took a full month to produce and customer delivery lagged by several days, blocking deeper analytics and new product development.
Solution
Luminate migrated to Snowflake as its cloud data platform, integrating dbt for transformation and Snowpark ML for machine learning, enabling independent scaling, real-time data sharing with clients, and a foundation for AI-powered analytics via Snowflake Cortex.
Tools & Technologies
What Leaders Say
“We have years of data that we were never able to glean deeper insights from before Snowflake. Essentially, we were just building rank lists.”
“We’ll be able to correlate between people who are fans of show X who are also fans of artist Y and brand Z. We couldn’t have done this before — and this breakthrough is thanks to having our unified data on Snowflake.”
“The ability to apply all the Python code and models directly on top of data is especially beneficial.”
Sign up to read complete case studies, access detailed metrics, and unlock all use cases.
Full Story
Luminate occupies a unique position at the intersection of entertainment and data. As the company behind the iconic Billboard charts, it processes more than 1 trillion data points daily from hundreds of verified sources across music, film, and television—serving major record labels, studios, talent agencies, and financial institutions who rely on that intelligence to make consequential decisions.
Before moving to Snowflake, Luminate ran its data operations on on-premises Spark and SQL Server infrastructure. That architecture could not keep up. The company received 3.5+ terabytes of data daily in multiple formats and formats, but end-of-month market reports took an entire month to produce. Customer data delivery lagged by several days. The team could generate rankings but struggled to derive deeper insights from its historical datasets, and cross-industry analysis—linking music consumption to television viewership to brand affinity—was effectively out of reach.
The transition to Snowflake brought a centralized data lake architecture with independent scaling of compute and storage. Luminate integrated dbt for data transformation and Snowpark with Snowpark ML for advanced analytics and machine learning experimentation. Snowflake’s secure data sharing capabilities enabled the company to deliver data directly to clients without manual file transfers. The consolidated platform became the foundation for building new data products at speed.
The results were immediate and measurable. Daily processing speed increased by 334%. Delivery of customer data fell from several days to minutes. The company launched its Streaming Viewership Model in beta in 2023—a product that combines structured metadata with unstructured sources to model streaming consumption across platforms—something impossible to build on the previous stack. Luminate can now correlate fans of a television show with fans of a music artist and brand affinities across the full catalog of historical data.
Luminate is now piloting Snowflake’s Cortex Analyst and Cortex Search capabilities to build AI companion tools that allow customers to query its data in natural language. The company’s evolution from a ranking list producer to a cross-industry intelligence platform reflects a broader shift in entertainment data: the value is no longer just in the charts, but in the connections between them.