Preventative Maintenance

Sensor data rapidly streams into companies and quickly grows to terabytes. Use GDP to predict when a piece of equipment may fail and then fix it before it breaks. With Neo4j, a large European communications company was able to represent the entire network in a flexible inventory management and support system that enabled rapid analysis of potential network outage scenarios, weak points with equipment where additional redundancy would be needed and eliminated the week long duration previously required to model the network impacts during planed infrastructure maintenance.

Resource Optimization

By analyzing resource utilization and adjusting based on changing conditions, companies can make the most of their finite resources. GDP brings together all the data and processing engines needed to model resource requirements and adjust in real time. With Neo4j, one of the world's largest logistic carriers was able to expand their real-time parcel routing capabilities to over 3K per second with a sustained workload of over 5M per day while handling daily changes to the logistics network with dynamic routing from any point to any other point.

Behavioral Insight

Historical pattern recognition with real-time data capture and analysis can show you where and how to intervene before it’s too late. Predict likely outcomes and take action that maximizes positive (or minimizes negative) results. With Neo4j, one of the world's largest providers of IT infrastructure, software and services needed to use always updating network topology information to respond to and identify root problem causes with minimal handling by human operators, grouping of redundant network alarms and automating the response for certain types of network events to minimize predictable future outages.