Free White Paper on Predictive Analytics

Thanks for coming to the Decision Management Solutions Predictive Analyatics hub. Here you can find additional information about using Decision Management to put predictive analytics to work as well as links to blog posts about predictive analytics.

Applying predictive analytics to operational decision making is the next wave of business innovation. Operational decisions drive interactions and determine the actions taken by an organization. Operational decisions are critical to how an organization treats, and is perceived by, its customers, its partners and its suppliers. Decision Management is the framework needed to fully exploit this opportunity.

Interested in how to effectively deploy predictive analytics in operational decisions?
Download our white paper Putting Predictive Analytics to Work.

Learn more about predictive analytics and decision management at our blog, JT on EDM. You can subscribe to the blog here.

Recent Blog Posts on Predictive Analytics

• Taking the question out of questionable claims
• To Hell with Business Intelligence, try Decision Management.
• Predictive analytics in marketing decisions
• Analytics run amok?
• Data Mining or Predictive Analytics?
• Mr Obama, smarten these systems!
• Transforming retail with analytics and decision management
• Making Better Business Decisions in 2009
• All Predictive Models Are Wrong - So What?

Blog Posts and Podcasts about Predictive Analytics World 2009

• PAW: Five Ways to Lower Costs with Predictive Analytics
• PAW: SAS and the art and science of better
• PAW: The High ROI of Data Mining for Innovative Organizations
• PAW: High-Performance Scoring of Healthcare Data
• PAW: Completing the visitor targeting cycle
• PAW: New Challenges for Developing Predictive Analytics Solutions
• PAW: Predictive modeling and today's growing data challenges
• PAW: The unrealized power of data
• PAW: Cross Industry Challenges and Solutions in Predictive Analytics
• PAW: Predictive Modeling for E-Mail Marketing
• PAW Analyzing and predicting user satisfaction with sponsored search