Here at MediaMath, we’re quite fond of data. It would be surprising to hear someone say they’re not fond of data, of course, but we’ve spent the last 18 months proving to ourselves and our clients that we really mean it. Our company is built around driving concrete, measurable results, and our clients – both internal and external – have sophisticated analytics teams that want access to the data we generate for their own analysis, owned marketing, budgeting, and more. In this post we will describe the journey from data warehouse to data platform and the success of ditching our […]
When a service grows in size and complexity, we add more tests in order to maintain test coverage. Having proper test coverage allows us to change or add new features and be reasonably confident we didn’t break any existing features. This is especially important for “bidder”, the name of our real time bidding service, where even a small unexpected downtime or bug can have major consequences. Bidder interacts with ad exchanges through http requests to place bids on advertisement opportunities (webpages, mobile apps, etc.) for our advertisers. As bidder increased in features and handled more bid opportunities (millions of bid […]
Last week, MediaMath’s hosted its global hackathon and what we hope will be the new template for internal technology events. MediaMath has hosted a number of hackathons in the past, and each one has seen more than its share of ambitious ideas and ingenuous solutions to everyday problems. This iteration was unique for a number of reasons—the 24-hour time-frame and global participation—but it demonstrated once again the energy and ingenuity of our team here at MediaMath. A snapshot of the hackathon, by the numbers… ~73 participants 14 teams/projects 24 hours to hack 8 locations: NYC, San Francisco, London, Berlin, Cambridge, Oregon, […]
Two weeks ago, engineers, developers and data scientists from all over the country packed into the Midtown Hilton in New York Spark Summit East 2016, the largest big data event focused on Apache Spark. MediaMath’s SVP of Data Science, Prasad Chalasani, partnered with Ram Sriharsha, a Senior Member of Technical Staff at Hortonworks to demonstrate how and why and why they used Spark in Monte Carlo Simulations to measure ad lift, or the behavioral effect that advertisements can have on consumers. Watch Prasad’s presentation in it’s entirety below: Most traditional applications of Spark involve massive data-sets that already exist. A less-commonly encountered use-case, but […]
I was at The Free and Open Source Developers European Meeting 2016. Commonly shortened to FOSDEM, the event brings thousands of people in the free and open source software community from all over the world to ULB, Brussels, to exchange best practices, share new releases, and generally discuss the state of open source development. The weekend was frighteningly dense (569 speakers! 618 events! 52 tracks!) so there’s very little hope of writing a full summary without the help of a small army of engineers. Based on the small sample of talks and panels I did get to attend, a few […]
Last month at the New York Scala Meetup, Owein Reese introduced the Autolifts library in Scala. Autolifts takes advantage of Scala’s advanced type system to yield a set of abstractions for working with complex objects. In this talk, Owein introduces the concept of lifting and why you might want to incorporate this pattern in your code. The library takes that concept, mixes it with dependent types and implicit extensions to automatically lift in a type safe manner. These extensions simplify code, reducing boilerplate while making code more easily understood and maintained. Thanks to Hakka Labs for recording and producing the video of this talk.