Resources - Videos
Unparalleled Graph Database Scalability Delivered by Neo4j 4.0
This session features Dr. Alessandro Negro, noted graph database author and Chief Scientist at GraphAware, along with Patrick Wall, Director of Product Marketing at Neo4j. During this webinar, GraphAware explores the powerful scalability features of Neo4j 4.0 in a live demo using the COVID-19 Open Research Dataset.
Knowledge Graphs in Action
In this presentation, you’ll learn how companies are building Knowledge Graphs with Neo4j and the Hume platform in order to surface previously undiscoverable insights. We’ll go over the process of analysing unstructured data using Machine Learning techniques and how graphs are a wonderful representation for storing Knowledge, making it naturally connectable. Lastly, a Graph Visualisation demonstration will take place, showing new insights discovered from the results of the previous operations.
Graph Hyper-Growth Ahead: 5-Minute Interview with Kyle McNamara
Interview with Kyle McNamara, CEO, Americas at GraphAware, about how GraphAware works alongside Neo4j (conducted at GraphTour DC 2019)
To Be or Not To Be, Neo4j Full Text Search Tips and Tricks
Christophe Willemsen, CTO at GraphAware, goes over some tips and tricks on Relevant Search with Neo4j’s Lucene based search engine.
Social media monitoring with ML-powered Knowledge Graph
Ever wondered how ML can be used to build a Knowledge Graph to allow businesses to successfully differentiate and compete today? We will demonstrate how Computer Vision, NLP/U, knowledge enrichment and graph-native algorithms fit together to build powerful insights from various unstructured data sources.
It Depends (and why it’s the most frequent answer to modelling questions)
The answer to most general purpose graph modelling questions is “it depends”. This talk demonstrates the pitfalls of modelling without knowing use cases- it shows how two sets of people can produce two different models for the same set of data elements, and how use cases should guide the model.
Fix your microservice architecture using graph analysis
So, for your brand new project, you decided to throw away your monolith and go for microservices. But after a while, you realize things are not going as smoothly as expected ;-)
Hopefully, a graph can help to detect antipatterns, visualize your whole system, and even do cross-service impact analysis.
In this talk, we’ll analyze a microservice system based on Spring Cloud, with jQAssistant and Neo4j. We will see how it can be helpful to answer questions like:
do I have anti-patterns in my microservice architecture ?
which services / applications are impacted when doing a database refactoring ?
is my API documentation / specification up to date ?
how to get an up to date visualization of my whole system ?
and more !
Challenges in knowledge graph visualization
Visualizing a complex graph is a task of graph simplification and providing well-thought visual cues, the best UI goes unnoticed. This talk will summarize current approaches and present a novel user interaction pattern, which takes advantage of a performant Neo4j graph engine.
Using Knowledge Graphs to predict customer needs, improve product quality and save costs
Alessandro Negro, Chief Scientist at GraphAware, delivers a presentation called Using Knowledge Graphs to predict customer needs, improve product quality and save costs during the SmartData Summit 2019 in Dubai.
GraphAware Audit Module Overview & Demo
The GraphAware Audit module seamlessly and transparently captures a full audit history who, when, and how a graph was modified.