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Data Science Delays! How to develop mission critical analytic deployment capabilities.
Session Time and Date
Tuesday, May 23rd from 1pm – 2pm CDT
How To Attend A Live Conference Session
Steps to Follow
- Click the link below to attend:
- Name and Email
- Join the conference session by clicking the link on the GoToWebinar confirmation email
To gain in-market competitive advantage, enterprises are leveraging the new wave of applied data science and analytics. The use-cases are myriad, including efficiently improving customer acquisition and pricing power, while simultaneously reducing customer churn and overall campaign risk. Companies are investing significant time and resource to analytic model creation. But, few are asking the question: “What do I do with this model once I have created?” or “How do I compare a model built in R with one from Python?” Turn to any of your fellow analytics professionals, and stories abound with comments like “Why did that take so long to measure?” or “Why does it take 6 months to get an improved churn model”? Part of the problem is that organizations are not prepared to quickly and efficiently deploy and iterate on the data science models they are creating.
This tutorial introduces principle concepts, tools, and methodologies which allow an organization to deploy and evolve mission critical analytics in a fast, safe, repeatable, and scalable manner. The tutorial will be relevant for deploying a wide range of analytics from simple as thresholds to complex machine learning models generated by the latest tools. Topics covered will include the primary concepts of Analytic Engines, Model Interchange Formats, Analytic Lifecycle Management, and Analytic Deployment Metrics and Benchmarks. Finally, Garrett will walk the audience through real world analytic deployment scenarios that can be used in their own organization.