Collaborative Power & Scalability

RapidMiner Server makes it easy to share, reuse and operationalize the predictive models & results created in RapidMiner Studio. RapidMiner Server’s central repository & management, dedicated computation power and flexible deployment options support analytic teamwork and rapidly put results into action.

Optimize Data Science Teamwork

Server-based environment facilitates sharing of data sources, analytic processes & best practices

 

  • Dashboards & user management functions
  • Shared repositories, version control and security features

Flexible execution options streamline deployment, maintenance & embedding of analysis

 

  • Business app integration & Web-service APIs
  • Automated processes with event scheduling & triggers

Scalable architecture increases computational power

 

  • Run big jobs on enterprise hardware freeing up local systems

Seamless Deployment, Management & Collaboration

Access, reuse and share processes &  data sources

Run processes on enterprise hardware from anywhere

Schedule or trigger event-driven model execution

Embed reliable results into business processes

Manage models, user administration & security

Collaboration

Shared server-based repository

 

  • Interactive dashboards
  • Version-control & security features

Centralized teamwork environment

 

  • Reusable building blocks, templates & processes
  • Storing of models in central repositories for reuse in other processes and projects

Computation

Scalable processing architecture

 

  • Server-Based Execution
  • Real-time Progress Monitoring

Flexible compute environment

 

  • In-Memory analytical algorithms and computations
  • Cluster support and distributed process execution engine

Scheduling

Productively deploy processes
  

  • Scheduling of workflow executions
  • Set up actions based on a triggered event
  • Remote execution of analysis processes

Automate deployment processes

 

  • Model retraining and scoring

Management

Dynamically and continuously update models

 

  • Individual and customizable processes to check for accuracy drifts or shifts
  • Triggering of model updates when needed
  • Alerting if model accuracy cannot automatically be restored

Monitor the system and manage user rights

 

  • Logging, auditing and version control
  • Significant flexibility to control access – groups, users, model, data,

Integration

Embed analytic results

 

  • Support for all major BI and data visualization vendors
  • Generic web-service connector

API & Web service deployment

 

  • Web services / processes can deliver XML, JSON, static / dynamic visualizations and binary files among others
  • API level integration with servers, data bases
  • Out-of-the box connectors for applications such as Salesforce