by Bill Jacobs, Data Center Knowledge
Deployment of predictive analytics to production will deliver operational, performance and risk improvements across large organizations in 2015. Whether by integrating on-demand analytics into BI dashboards and reports, or by computing predictions as part of the business application logic, predictive analytics will go production for many this year. For those already in production, historical methods such as re-coding predictive models into Java or C++ prior to deployment have reached end-of-life. As application teams accelerate model deployment cycles, lower development costs and minimize coding inaccuracies, direct deployment of new models is needed. For IT, this means onboarding of new production systems that compute predictions, and with them, come challenges.
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