As we continue to understand the "Graph" way of perceiving and analyzing this world, we're excited to announce our next meetup with the Dallas Elastic Fantastics group.
In this session, we will review the Elastic Stack product offering and then quickly deep dive into machine learning and graph capabilities with demos of scenarios.
Built on an open source foundation, the Elastic Stack lets you reliably and securely take data from any source, in any format, and search, analyze, and visualize it in real time.
Complex, fast-moving datasets make it nearly impossible to spot infrastructure problems, intruders, or business issues as they happen using rules or humans looking at dashboards. Elastic machine learning features automatically model the behavior of your Elasticsearch data — trends, periodicity, and more — in real time to identify issues faster, streamline root cause analysis, and reduce false positives.
There are potential relationships living among the documents in your Elastic Stack; linkages between people, places, preferences, products, you name it. Graph offers a relationship-oriented approach that lets you explore the connections in your data using the relevance capabilities of Elasticsearch.
Here are a few interesting places to go for more information: Getting Started with Elastic Stack, Measurement Data Webinar with Demos, Graph Overview, Machine Learning Introduction