I am speaking at the Bay Area SAS User Group October 15 at 3pm on Improving Analytic Results with Decision Modeling
Established analytic approaches like CRISP-DM stress the importance of understanding the project objectives and requirements from a business perspective, but to date there are few formal approaches to capturing this understanding in a repeatable, understandable format.
This presentation will discuss how decision modeling closes this gap and improves analytic results. Decision modeling is a successful technique that develops a richer, more complete business understanding earlier, resulting in a clear business target, an understanding of how the results will be used and deployed, and by whom.
It also reduces reliance on constrained specialist resources by improving requirements gathering, helping teams ask the key questions and collaborate effectively across the organization. The presentation will show how decision modeling can be used in a wide range of analytic projects in various industries. Attendees can download the white paper on decision modeling for analytics projects here.
Members can RSVP here.
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