RampUp 2020: RampUp for Developers Recap

LiveRamp’s biggest event, RampUp, took place on March 2nd and 3rd in San Francisco, at the Fairmont Hotel, the InterContinental Mark Hopkins Hotel, and the Masonic Center. This year, for the first time, during what was formerly known as Pre-Conference, during Day 1 of RampUp, participants could take part in the Innovation Studio, before the […]

In The News – Built In Boston: “Why LiveRamp Turns to Python for Major Projects”

The LiveRamp Boston Engineering team was recently featured in Built In Boston. Built In Boston is the online community for Built In Boston startups and tech companies. The article, entitled “Why LiveRamp Turns to Python for Major Projects,” focuses on LiveRamp’s use of Python to help the engineering team advance to the next stage of […]

Winter 2020 Speaking and Events

LiveRamp’s Engineering Team will be speaking at number of conferences and events in the coming weeks. You can see them speak at the following:   4th Annual Global Artificial Intelligence Conference Who: Akshaya Aradhya, Director of Engineering at LiveRamp When: January 21-23, 2020 Where: Santa Clara Convention Center The Global Big Data Conference’s 4th Annual […]

New to RampUp 2020: RampUp for Developers

Introducing RampUp for Developers RampUp is LiveRamp’s proprietary conference, where industry leaders discuss Mar Tech, customer experience and data regulation. This year’s conference will take place on Monday and Tuesday, March 2nd and 3rd, in San Francisco. This year, we’re introducing a new track; RampUp for Developers.  About RampUp for Developers RampUp for Developers is […]

Joining Petabytes of Data Per Day: How LiveRamp Powers its Matching Product

Our data matching service processes ~10 petabytes of data per day and generates ~1 petabyte of compressed output every day. It continuously utilizes ~25k CPU cores and consumes ~50 terabytes of RAM on our Hadoop clusters. These numbers are growing as more and more data flows through our platform.  How can we efficiently process the […]

Migrating a Big Data Environment to the Cloud, Part 5

What next? In the previous posts about our migration, we asked ourselves: Why do we want to move to the cloud? What do we want our day 1 architecture to look like? How do we get there? How do we handle our bandwidth constraints? The last and most exciting questions are, “What comes next”?  “How […]