As a leading DSP with billons of online ads running through our platform every day, one of our biggest problems is how best to frequently report attribution data (which ad led to which action, like a sale or online signup) to our clients in a reliable way. The problem we are tackling, in numbers: A) 30-day impression volume = 35 – 40 billion records B) 1-hour event/click volume = 15 – 20 million records We need to join B (events) with A (impressions) twice every hour (once for event and once for clicks), find the matching records, perform complex sequencing […]
Ram Narayanan is the Senior Director of Database Architecture and Operations at MediaMath. He has exposure and experience in architecting and building a wide variety of data products at scale in a range of medium to big data platforms, from MySQL/Postgres/Oracle to Hadoop and other cloud-based big data offerings. Prior to MediaMath, Ram worked as a Data Architect on a variety of data platforms in a range of verticals including retail, banking, and telecom. Ram is committed to building and automating the right systems at scale, and is always interested in learning and implementing new technologies.