BEGIN:VCALENDAR VERSION:2.0 PRODID:-//hacksw/handcal//NONSGML v1.0//EN METHOD:PUBLISH BEGIN:VEVENT DTSTAMP:20260421T155212Z DESCRIPTION:Click for Latest Location Information: http://edw2018.dataversi ty.net/sessionPop.cfm?confid=121&proposalid=10025\n

During his talk, Sean Hanlon, Data Scientist at Dataiku, maker of the collaborative advanced ana lytics and ML platform, will demonstrate how companies can predict how much net profit each new individual customer is going to generate. In other wor ds, the audience will get a first-hand account of what it takes to build a real Customer Lifetime Value predictive project from scratch. During this 3 0 minute deep dive into this widely sought-after use case, Sean will walk t he audience through the development of an end to end predictive data flow & ndash; covering design, data exploration, collaboration, and production cap abilities.
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\nFor this project, Sean will leverage historical c ustomer data (age, gender, location, purchase history, location, etc.) that he will clean and merge using both a clicker and coder approach. After hav ing enriched this data with location data, Sean will build a model to predi ct how much money a customer will spend, based on his or her first interact ions on the website. From there, Sean will be able to deploy this end-to-en d flow (from historical data to predicted data) and apply it to incoming ne w data to score all new incoming customers. This talk is designed for both a technical and non-technical audience.

\n DTSTART:20180425T094500 SUMMARY:Data Science in Practice: Deep Dive into Building and Running a Cus tomer Lifetime Value Predictive Data Flow DTEND:20180425T101459 LOCATION: See Description END:VEVENT END:VCALENDAR