Webinar
Cutting Data Costs for AdTech:
Reduce costs, increase margins, retire younger
The Ad Tech market holds incredible opportunity for those who can efficiently analyze massive volumes of data from an increasing variety of sources. But that high-volume data processing comes at a price – a cost that can make or break a growing Ad Tech vendor.
Managing data costs are an essential success factor for Ad Tech, whether a publisher optimizing revenue, or a DSP finding the perfect balance between targets and costs. It’s not as simple as just using the cloud or open-source, which can have hidden operational and technical costs. And of course, any solution needs to have the right capabilities for an Ad Tech company to squeeze as much value as possible out of all that data.
Join this webinar to hear:
- The most common data processing techniques in use by Ad Tech companies today – and the pros and cons of each approach
- How companies dramatically reduce their infrastructure bills by rethinking their approach to the cloud
- The hidden costs of data processing, and how to evaluate new technologies so you won’t be surprised later on
Register now to view the recording on-demand.
About the Speaker:
AdTech industry veteran Ruben Padron is the founder of Padron Analytics, a data science consulting firm dedicated to the exploration of data to grow and optimize businesses. Specializing in statistical modeling and data visualization, Padron Analytics' clients include online publishing platforms, mobile app developers, as well as online and mobile ad networks. Ruben has also served as head of analytics for both Metaresolver and SAY Media, where he lead teams of data scientists focused on building data-driven solutions to optimize ad performance. Through his work at Yahoo! in search analytics and Gaia Online in game analytics he played a pivotal role in guiding product strategy for mass market online services. At Nielsen NetRatings he led research teams dedicated to developing reporting methodologies and standards for Web measurement that defined online media measurement standards.