The fourth largest independent TV station owner in the U.S. shares news and entertainment across 60 television stations in 42 markets. To understand audience engagement and measure both national and local media group performance, the company ingests and analyzes billions of rows of operational and TV ratings data from sources like Nielsen and Comscore.
However, the company’s legacy data analytics architecture required constant administrative oversight, basic queries took hours to run, and it could take 3 months to add a new data source – all of which stifled data exploration, significantly delayed insight discovery, and led to missed revenue opportunities. Furthermore:
- The legacy architecture was couldn’t handle the volume of data necessary for 2 reports that were key to driving revenue: a year-to-date data by market analysis and a year-over-year sweeps rating comparison. The BI team tried to build these reports in Tableau for 2 months before abandoning the project.
- Scale and performance limitations made it impossible to effectively analyze data across sources and filters could take an hour or more to load.
- The company also lacked a way for the BI team to collaborate on analytics with their line of business counterparts or quickly share new insights with TV station leaders.
With Sigma, the BI team built a live dashboard with ratings and revenue data that now informs critical business decisions. The content team monitors and optimizes audience engagement. The sales team drives revenue by leveraging data to sell advertising placements based on a mix of programming, demographics, and market.
Direct access to Snowflake
Sigma was purpose-built for Snowflake and cloud data warehouses. The BI team now has direct access to live data in Snowflake, ensuring that everyone is always looking at the same current data. Station leaders have instant access to the information they need to make informed decisions while data stays safe in Snowflake.
Unlimited scale and speed
Sigma is a cloud-native solution delivering unlimited scale at cloud speed - no summaries or aggregates necessary. The BI team can now easily analyze and filter billions of rows of ratings data across multiple sources, enabling them to rapidly drill down into data without rendering or latency delays.
Self-service data exploration
Sigma’s spreadsheet interface makes iterative ad hoc analytics available to anyone. Today, the BI team has a single source of truth for data and can easily add new sources to analyses without help from the data team, which has accelerated and improved insights.