Collaboration & Deployment

 

IBM SPSS Collaboration and Deployment Services lets you manage analytical assets, automate processes and efficiently share results widely and securely.
Because when the people developing and the people using analytics can collaborate, your analytic efficiency increases.

Key benefits of using IBM SPSS Collaboration and Deployment Services:

  • Bring control to analytical processes by centralizing and automating the evaluation and deployment of models.
  • Enhance model accuracy through champion and challenger testing.
  • Deploy scores generated by models in real time to support decision-making.
  • Integrate analytics within key business processes.

Collaborate

Reports and models will be difficult to recreate if they were lost or destroyed, making collaboration a key concern in analytical asset management. In addition, as various users work together in analytical projects, it is important to track who has access to analytical assets and what changes are made to them.

With IBM SPSS Collaborate and Deployment Services, you can:

  • Share and search for analytical assets in the centralized repository
  • Reuse and standardize analytical work for more effective results
  • Protect and audit analytical assets through user access control and version tracking

Automate

Automation enables your organization to make analytics a core component of daily decision-making.

With IBM SPSS Collaborate and Deployment Services, you can:

  • Increase productivity by automating manual analytical tasks
  • Automate model evaluation and refresh to ensure relevant results
  • Construct flexible, repeatable analytical processes that can be activated based on demand or triggered by events

Deploy

Deployment bridges the gap between analytics and action by enabling organizations to operationalize, which means embedding analytic results in front-line business processes.

The real-time scoring services in IBM SPSS Collaboration and Deployment Services enable you:

  • Use information gathered during the time of the interaction and historical data to determine the score that recommends the best product or service to offer to the customer type
  • Seamlessly integrate with existing applications using standard programming interfaces, such as Web Services.