A Data Science Central Community
DATA MINING: FAILURE TO LAUNCH
How to get predictive modeling
off the ground and into orbit.
View schedule and register for
an upcoming live interactive event.
The vast majority of BI professionals are excited about the prospects of data mining, but are fully mystified about where to begin or even how to prepare. Of those who did initiate a modeling initiative, a recent data mining industry survey of predictive modeling practitioners reports that 51% of data mining projects either never left the ground, did not realize value or the ultimate results were not measurable. In most cases, those who attempted an implementation ended up building excellent predictive models that answer the wrong questions. This is precisely like placing a perfectly good rocket upside down on the launch pad.
So, how does one approach an intangible, cryptic, seemingly immeasurable technology? Beyond the inherent up-front risks of engaging in what is essentially a discovery process, just identifying a starting point can be intimidating and mystifying. Despite its elusive nature, data mining technology has surpassed the flash-in-the pan "miracle tool" stigma with widespread and sustained success stories highlighted in mainstream publications, along with recurring case studies of improved operational efficiencies, enhanced business intelligence and residual payback.
For any organization with annual revenues more than $50 million, employing data mining technology is not a matter of whether, but when. Attend this free webinar to learn how to get started with data mining and overcome limitations that cause data mining projects to fall short of their potential.
This webinar is intended for stakeholders, functional managers and business practitioners in business, industry, government and academia, who have made substantial investments in data collection, storage, retrieval, visualization and basic analysis but may not have the technical or strategic experience necessary to chart an effective roadmap to uncover the valuable predictive insights hidden within their existing data. No prior knowledge is required. The webinar will cover: