Create a Quine Icon Library with Python
Add some flair to your Quine streaming graph visualizations while learning about the API at the same time.
Dynamic Duo: Quine & Novelty Detector for Insider Threats
In a big update to the VAST Advanced Persistent Threat blog, we demonstrate an end-to-end Quine plus Novelty Detector workflow.
idFrom(): the simple function that’s key to Quine streaming graph
idFrom() seems like a simple function for generating node IDs but it is the key to Quine’s ability to find complex patterns in high volume event streams.
Using Indicators of Behavior (IoB) Analysis for IoT data
Indicator of Behavior (IoB) analysis is extending beyond the cybersecurity domain to offer new value for finance, ecommerce, and especially IoT use cases.
Quine’s Real-time Temporal Event Sequencing Produces New Insights
Quine’s standing queries, idFrom + deterministic labelling can be use to efficiently create any subgraph you need (e.g. sequence based) in real time. This makes alerts more timely and root cause analysis more efficient.
Graph Neural Networks for Quine
Quine 1.5 includes support for graph neural network techniques like Node2Vec and GraphSAGE. This post provides an overview and tutorial.
Categorical Data: An Untapped Source of Real-Time Insights
Categorical data is an oft-ignored source of valuable business intelligence. Quine makes it easy to process categorical data with your existing ETL pipeline.
Quine Streaming Graph: A Year in Open Source
thatDot’s iteratively improving the developer experience: who is Streaming Graph built for, what jobs do they tell us they need to get done.
Quine 1.4.0: Scale, Stability, Supernode Mitigation
Quine 1.4.0 release includes improvements for scalability, stability, and supernode mitigation plus work key to reaching 1M events/sec.
Why Digital Twins Need to Go Real Time
For digital twins to be truly useful in business operations, they must be able to drive actions and do so the instant an issue emerges, perhaps even beforehand.