Todays' graph databases have a strong focus on storage & traversal of data graphs. Most often, data analytics is left to other platforms.
Predictive Graph. is different and provides an analytics first approach:
We start from a real-time analytics platform and integrate with a graph engine.
The benefits of this holistic approach are obvious:
Deep link analysis, uncovering connections with fast traversal, answering unanticipated questions side-by-side with advanced analytics & machine learning.
Todays' business requirements have a strong focus on event-oriented real-time data processing:
Events originate from audience or customer interaction, devices that send telemetry events and more.
Whether one needs to take action with real-time advertisals, content recommendations or any other real-time response, the required approach is always the same:
Events have to be ingested into your data graph in real-time.
Predictive Graph. responds to this technical fact and integrates with a world-class streaming platform.
Suppose your security analysts leverage Predictive Works. prediction templates to identify malicious network behavior that indicates a cyber attack.
And, your maintenance team uses prediction templates to answer the question whether your production line will probably be down within the next 24 hours.
But, imagine if you could understand that the detected cyber attack is directly related to the predicted production downtime.
Predictive Graph. empowers you to connect information independently collected by different business areas and gain a hollistic view of your business in real-time.
This is what we mean by information superiority. Do you agree?
Your information universe is spanned by three temporal dimensions:
Hindsights. Historical information that describes what happened in the past and often contains causes for effects experienced in the present and future.
Insights. Present information that describes what happens and causes future effects.
Foresights. Future information that describes what probably will happen and what has to be done to make desired effects happen.
Predictive Graph. unifies these dimensions into a single 360° view, connects causes and their resulting effects and empowers you to turn information into business knowledge.
You are not interested in cyber defense? Predictive maintenance is not on the roadmap?
Suppose you are a media company and your core business is publishing valuable content.
We are convinced that there is a strong need to leverage social listening templates and identify breaking stories before they go viral.
Or respond to changing audience interests and deliver matching content and advertisals in real-time. You are no media company?
Use cases for cross-area and cross-sights connections based on Predictive Graph. and Predictive Works. are limited by imagination only.
Do not hesitate to contact us and talk about your specific use case.
Apache Kafka is a distributed real-time streaming platform capable of handling trillions of events a day.
Predictive Graph. integrates with Kafka event streams to either ingest any kind of events into your data graph or send graph-based event streams to other Apache Kafka consumers.
JanusGraph is a scalable graph engine optimized for managing and querying distributed data networks containing hundreds of billions of nodes and edges.
It supports thousands of concurrent users executing complex graph traversals in real time.
Predictive Graph. integrates with JanusGraph engine to support complex graph traversals in real-time with Gremlin query language.