Organisations do not suffer from a lack of data or qualified people who analyse it and draw conclusions but rather from the size of relevant data sets and the limited amount of time skilled people can spend on exploration and analysis. In this blog post we show how Hume Alerts can be used to solve this issue.But before we get started, I would like to take you to a very analog place, where, even without high speed internet, Alerts work.It is a sunny morning in early April in the North of Sweden, the air is cold and crisp. As I...
Not so long ago, our very own Luanne gave an amazing talk titled Maltaware: Discovering what to drink with Neo4j on Nodes2020. Luanne demonstrated the value of graphs, and why they are the perfect fit for recommendation engines with an example of a whisky recommendation engine. Let me quickly walk you through a summary of why graphs and recommendation engines go together so well.Recommendation engines are everywhere - they are used to suggest products you may like, people you may know, places you could enjoy traveling to, and more. Recommendation engines provide immense value to businesses as they improve user...
GraphAware is now going through an extremely exciting phase. In 2020, we launched our own amazing product Hume, the only graph-powered insights engine in the world, which helps companies shed light on their complex data and make smart decisions. Since then, we have been rapidly growing in all aspects. Our ambitious plans will need plenty of talented people, who want to have a direct impact on a company’s success. Right now, we are already advertising for multiple vacancies, and the number will only grow in the coming months (check out our career page if you are already intrigued).I believe it...
Before I started at GraphAware I spent many years in research, both academia and industry, focusing my attention on machine learning and image processing.So when I knew that my first project was meant to be integrating image recognition in Hume, I was excited.Everything started during my first day in GraphAware. I was talking with Alessandro, the Chief Scientist, who was in charge of my onboarding. He asked me, with my past experience in image analysis, if I would be able to draw out a system for face recognition applied to an eventually growing set of pictures.I knew it was not...
GraphAware is proud to announce the 2.9 release of Hume. With this release, Alerts are available in Hume, a feature that greatly simplifies the daily work of analysts, data scientists, investigators, and data-savvy business users. And there is more: Stay on top of changes in your data with automated Alerts Super-charge Actions by tapping into additional Neo4j data Bring your graph onto a map with Hume MapsStay on top of what’s happening - effortlesslyWith Hume Alerts, it is possible to monitor data sets and receive notifications on relevant changes. There is no more need to proactively explore data in search...
When we started our journey with Neo4j over ten years ago, we were just a bunch of passionate techies trying to convince the world about the power of graphs. We were blogging, running meetups, writing open-source code, speaking at conferences, trying to preach graphs to a like-minded crowd.I could not be more excited to hear the news of the latest Neo4j funding round. $325M is a substantial amount of money, and I am convinced it will help make the Neo4j product even better, faster, and more scalable.The market for graph databases in the context of real-time transaction processing has already...
Say you have a graph-based project in mind. Be it research in life sciences, a fraud detection machine, or possibly a recommendation app. Anything that relies heavily on relationships between data points is a good case for a graph.First, you will need a graph database. Let’s assume that you have picked Neo4j as your go-to technology. Good choice. Honestly. They defined the market and still are the preferred solution by the majority of customers.Now you have a solid technology foundation. Your connected data can live someplace. The next part is to get your project moving.Build or buy?There is a decision...
It has been over 8 years since I’ve written the first lines of code for the GraphAware Neo4j Framework as part of my MSc. thesis. That’s when the name GraphAware, as well as the (then) one-man show Neo4j consulting company was born. It is therefore my bittersweet duty to take you on a small trip down the memory laneand announce that we have decided to discontinue the development and support of the Framework and all of its modules.In this blog post, we briefly cover the bits of Neo4j and the GraphAware Framework history that are essential to understandingthe technical reasons...
GraphAware is proud to announce the 2.8 release of Hume, our graph-powered insights engine. The release adds further unique capabilities to Hume’s knowledge graph visualisation and graph data analysis capabilities. Analysts, data scientists, investigators, and data-savvy business users will profit from these benefits: Save permanently the insights you uncovered using Snapshots. With Snapshots, you can pick up your exploration at any time without worrying about changes in data or schema and, eventually, share with other analysts. Make graph patterns more evident by shortcutting a long path through a virtual relationship: Hume’s Virtual Relationships let knowledge graph managers and analysts cut...
CDC (Change Data Capture) is a well defined software design pattern for a system that monitors and captures data changes so that other software can respond to those events.CDC has many advantages compared to the traditional polling approach : All changes are captured: Intermediary changes between two polls are tracked and can be acted upon Real-time and low overhead: Reacting to CDC events happens in real time and only when changes happen avoiding CPU overhead of frequent polling Loose coupling: CDC send captured changes to messaging brokers, consumers can be added or removed on demand Applications of Neo4j Change Data...
