Published April 21, 2022

Better, Faster, Cheaper: How Ocient Analyzes Over 7 Trillion Data Points in Interactive Time to Deliver New Revenue and Cost Savings in AdTech

By Jonathan Kelley, Director of User Experience at Ocient

Challenged with a need to innovate quickly in the Campaign Forecasting space to pursue a $100M revenue opportunity, leading demand-side provider, MediaMath, turned to Ocient to develop a hyperscale data analytics solution powered by its enterprise data warehouse platform and team of industry experts.

With more than 3,500 advertisers relying on their demand-side platform and modernized ecosystem to solve complex marketing problems, MediaMath was already helping their clients deepen customer relationships across screens and around the world. But their advertising clients wanted the ability to scientifically leverage more granular campaign insights to forecast more accurately for future campaigns and reduce wasted or poorly targeted impressions.

With over 7 trillion data points that may need to be evaluated in a forecast query, harnessing a firehouse of data pouring in 365 days a year, 24 hours a day was critical. And when layering in seasonal changes and shifts, getting up to the moment, high-resolution insights is mission critical for demand-side providers like MediaMath to forecast and deliver on the most competitive and contextually relevant opportunities for their customers.

To give you a sense of why Campaign Forecasting for AdTech companies is undoubtedly a job that requires hyperscale tools:

  • Billions of rows with ~3,200 data points or more per column must be easily accessible within the data warehouse or database for a typical campaign forecasting workload of the size and scale of MediaMath’s
  • 7 trillion data points or more must be evaluated in a forecast query that must also run in a few seconds or less
  • 5 quintillion (or 5 x 10^15) possible combinations occur in just three critical columns (audience, contextual, and deal IDs) for a solution like MediaMath’s, demonstrating extreme cardinality of the data that must be supported

When you’re working with numbers like these, it’s imperative to have a finely tuned system that can not only run these types of workloads multiple times a day, but multiple times a second.

That’s why MediaMath chose Ocient to partner on the development, testing, and deployment of their hyperscale campaign forecasting solution. They required more than just a new piece of software or technology to operate at this scale. To get to market faster, they needed a true end-to-end solution, uniquely tailored to their use case and business requirements.

But don’t take my word for it. Hear from our customer, Chris Ingrassia, on about his experience working with Ocient on this next-generation solution and read our case study to learn more.

 

Whether you’re in AdTech or another industry, Ocient prides itself on partnering closely with customers to tackle their toughest hyperscale data challenges. Contact sales@ocient.com for more information or contact us via the website to book a demo.