Last week, Jeff Campbell and Scott Rosenblatt from Meltwater joined the Scrum Master Toolbox Podcast. In this mega-episode on change, Jeff (long time contributor to the Scrum Master Toolbox podcast) and Scott (Director of Engineering at Meltwater) share their experience with Agile adoption in a large organization.
Meltwater recently released a new product feature called Signals, which helps our customers to identify business-critical events.
In a previous post we introduced the concept of record linking, and presented our first approach for merging information from multiple sources for our Knowledge Graph.
In this second post, we share how we improved those initial models based on user feedback and analysis of learning features, and also present formal evaluation metrics.
Meltwater recently released a new product feature called Signals, which helps our customers to identify business-critical events. One of the technical systems powering these Signals is a custom-built Knowledge Graph.
In this post we explain how we created a record linking service that utilizes machine learning and big data tactics to cluster millions of related entities from various sources with high accuracy for our Knowledge Graph.
As we are going pretty deep into the material, this post is intended for software engineers with an interest in data science or data engineering.
The Meltwater Engineering teams have always been doing a lot of remote collaboration, due to the distributed nature of our company. Still, we have to get used to the work-from-home situation where we cannot even meet the colleagues in our own offices.
In this post Niall Burkley from our middleware team shares a simple standup routine to remind us that “we’re all people” after all. This can support your growth as a remote team.
You find more articles like these on Niall’s blog niallburkley.com.
In early spring 2018 Kubernetes went into Production at Meltwater and has seen great adoption from a lot of our engineering teams. Our Kubernetes cluster went from hosting 150 services at the end of 2018 to more than 800 services 9 months later.
As part of our involvement in the Cloud Native Nordics community, we recently gave a tech talk there where the team managing our Kubernetes cluster shared what they learned about scalability testing Kubernetes.