Optimize and automate decisions that can consistently generate successful outcomes
IBM® SPSS® Analytical Decision Management for Linux on System z enables organizations to optimize high-volume transactional decisions before deployment, so that they can consistently maximize outcomes. Using a combination of predictive models, business rules, optimization and scoring, the solution guides employees and systems to instantly make the best possible data-driven decisions.
SPSS Analytical Decision Management for Linux on System z combines the power of predictive analytics with the performance, scalability and availability of the System z platform. This enables businesses to adapt to increasing volumes of data and a growing number of users, while deriving greater overall value from everyday transactional decisions.
With SPSS Analytical Decision Management for Linux on System z, your organization can:
- Optimize transactional decisions that add up to a significant impact on the bottom line.
- Deliver recommended actions at the point of impact using advanced techniques and algorithms.
- Perform data mining and text analysis, based on predictive models, local rules, decision logic, scoring and optimization.
- Make real-time, adaptive decisions to help business users continuously improve models and maximize every outcome.
Optimize transactional decisions
- Develop new and reusable predictive analytic assets by leveraging existing structured and unstructured data.
- Measure trade-offs at the execution level by solving very large optimization problems comprised of millions of constraints and variables.
- Learn from previous decisions through repositories and feedback mechanisms.
Deliver recommended actions at the point of impact
- Use the strengths and analytics of existing databases, including IBM Cognos® Business Intelligence, IBM DB2®, IBM Netezza, Informix, Microsoft SQL Server, Sun my SQL, Oracle and Teradata.
- Automatically prepare, cleanse and transform data – in a single step – for the best possible analytics.
- Use an array of pre-built algorithms to mine millions of data records and create accurate predictive models.
- Automate and apply scoring, and deploy and distribute scores across the enterprise.
- Build enterprise-wide business rules within IBM Operational Decision Management to improve compliance, governance and speed.
Make real-time, adaptive decisions
- Combine new attitudinal, behavioral and transactional data with historical data to score a decision and receive the results in real time.
- Adapt insights through feedback mechanisms and predictive analytics.
- Refine the decision-making process by running multiple simulations and comparing the outcomes of different approaches (for example, by modifying variables such as cost and profit margin).
- Deploy the best-performing models.