Keys to the Commercial Success of
A workshop held in conjunction with
The Fourth International Conference on Knowledge Discovery and Data Mining (KDD '98)
New York City, August 31, 1998
Kurt Thearling, Exchange Applications
Roger Stein, Moody's Investors Service
Data mining is on the cusp of true commercial success. Commercial institutions are starting to move beyond pilot studies and research programs toward the production use of predictive models for real world business applications. While this is exciting, it is also where it gets harder.
Successful data mining in business doesn't come down to simply having a hot algorithm and giving it to an experienced modeler. Business users care about things such as database support, application integration, business templates, flexibility, scalability, real profitability, and other issues that have not historically been the concern of the KDD community.
From a development point of view, the core algorithms are now a small part, perhaps 10%, of the overall data mining application, which itself is only 10% of the business process that contains the application. This workshop focused on the remaining 99% so that commercial data mining applications are relevant to business users.
This workshop brought together a diverse group of developers, users, and integrators of business data mining applications. Five formal presentations were combined with two panel sessions a lot of discussion.
This web site is an archive of the materials, presentations, and write-ups from the workshop. The following materials are now available online:
- Problem Formulation and All That Other Stuff,
Foster Provost, Bell Atlantic
- Myth and Reality of Data Mining in Marketing Applications,
Yuchun Lee, Unica
- Success with Data Mining in the Business World,
Paul Maiste, PriceWaterhouseCoopers
- The Hardest Thing is Getting Into Peoples Heads,
Vasant Dhar, NYU
- How Data Mining Relates to the Rest of DSS,
Erik Thomsen, Dimensional Systems
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