This team better not mess up at work: Last year ads for more than 100 million Euro were booked through the sales tool they built.
A new profession is playing an important role in how content will be presented on Schibsted´s news sites: Data scientists. Meet the machine learning team!
Nothing matters more than speed for the iOS product development team in Schibsted News Media. Soon also VG will launch on their super-fast app.
Can news sites as different as Fædrelandsvennen and Aftonbladet be based on the same design elements? Yes, says the team that is building a design system for all of Schibsted´s publishers.
Media businesses looking to serve the interest of diverse societies need to reflect on how we implement new technologies. Artificial Intelligence is no smarter than the data it eats, and it is in our ethical and financial interest to think twice about what we put on its plate!
At Schibsted, we use data science to build models that aggregate user behaviors and preferences. Advertisers can combine these to allocate users in groups, known as targeting segments.
In the era of BigData, where the volume of information we manage is so huge that it doesn’t fit into a relational database, many solutions have appeared. Hadoop, Spark, NoSQL are great tools for a purpose, but they don’t fit 100% of the audience.
JSLT is a language for querying and transforming JSON that runs 9 billion transforms every day at Schibsted. We are now open sourcing it so anyone can use it.
Test Impact Analysis (TIA) is a modern way of speeding up the test automation phase of a build. It works by analyzing the minimum set of tests that need to be run after a change to production code.
Kotlin is the new chaos that suddenly penetrated all the tech teams all over the world. Google fully supported Kotlin, integrated it into their Android Studio IDE and considered it a stable language. As a result of this movement, soft or even brute actions need to be considered to be
Imagine this: You’re a marketplace website. You rely on content created by users to deliver a quality product to the general public, with minimum intervention from your side. Because at the end, you’re just a connection between the buyer and the seller. Now, how do you deliver the best user
In an earlier post we discussed a service to estimate the number of unique visitors to a website. In this article we explore the algorithms we used to build the system: HLL (HyperLogLog) and KMV (Kth Minimal Value) and evaluate each.
