DecisionBrain announces partnership for upcoming IBM Decision Optimization Center v4.0 release | Learn More

IBM Decision Optimization Center

An optimization platform to create, deploy and maintain fully scalable decision support solutions. Quickly, easily, efficiently.

Components

Seamlessly run multiple CPU intensive computational jobs locally or remotely and provides administrative tools to easily monitor and manage them.

Optimization Server

Seamlessly run multiple CPU intensive computational jobs locally or remotely and provides administrative tools to easily monitor and manage them.

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DATASHEET
Scenario Service

This service manages a hierarchy of scenarios organized into workspaces and folders. It provides an API to easily manage creating, renaming, duplicating and deleting workspaces, folders and scenarios.
Data Service

This service manages data in a relational database, indexed by scenarios. It provides an API to:
- Get a description of the database parameters
- Create /Read/ Update/ Delete rows
- Map data with in-memory representation
Web Frontend Service

Predefined Web User Interface that can be configured and/or
customized, with the possibility to fully replace it if needed.

READY-TO-USE-SERVICES

AVAILABLE TEMPLATES

CUSTOMIZABLE

DATABASES

Learn about the DOC by downloading the datasheet today
PDF

OR & DATA EXPERTS

DEVELOPERS

IT & DEPLOYMENT

PROJECT LEADERS

Focus on modeling competencies, rather than on IT complexities.

Benefit from open/modern technologies for scalability, extensibility and robustness.

Developing and Testing: unsynchronized development and parallel testing thanks to a clear separation of projects.
Deployment: local (Docker-compose) or industrial (Kubernetes/ OpenShift).

Build robust, easy to deploy/maintain applications.

Deployment: local or industrial, on the cloud or on premise, thanks to Docker-compose, Kubernetes and OpenShift.
Maintenance and Evolutions: fail-over and replay execution capabilities.

Standardize development and deployment practices improving teams’ efficiency.

Contribute: continuous feedback from business users during application development.
Collaboration: among data scientists, optimization experts, IT and deployment teams.