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Overview: The widespread use of predictive analytics has enabled organizations to more accurately predict their business outcomes, improve business performance, and increase profitability. As the sheer number of these models in the overall portfolio is coupled with growing requirements to demonstrate external compliance, it is imperative that the organization implements sound model management practices. Model management is not a one-time activity but an essential business process. This paper from SAS Institute presents SAS-based strategies for effectively managing predictive models in a production environment and introduced a new product, SAS Model Manager 2.1 for SAS 9.1.3.
Profit Acceleration Strategies for Mid Sized Companies
IT budgets are tight, but there is no leeway when it comes to staying competitive and profitable.
Certain mid-sized organizations are experiencing record...
Impact Business Performance with BPM
To maximize your chances for success, you need the ability to continually optimize, streamline and align business processes to meet changing business needs for greater performance. Business process management (BPM) from IBM can help.
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