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Can Predictive Analytics Ever be Automated?

May 23, 2017

Free

Session Time and Date

Tuesday, May 23rd from 2pm – 3pm CDT

 

How To Attend A Live Conference Session

Steps to Follow

  1. Click the link below to attend:
  2. Register
    • Name and Email
  3. Join the conference session by clicking the link on the GoToWebinar confirmation email

Presentation Description

There are not enough data scientists in the world to keep up with the demand for predictive analytics in business today. The good news is that the growth of data is continuing the bad news is that this only exacerbates the need for data scientists. The hope is that we can turn marketers and other business users into pretty good data scientists by giving them self-service and automated tools. Sometimes this has resulted in disaster. Sometimes this has resulted in success. In this talk I will review the challenges and opportunities of automating predictive analytics tools and show when and how to deploy them.

The attendee will learn:

  • When automated predictive analytics tools are appropriate
  • How to evaluate predictive analytics tools
  • Best practices for training and organizational structure
  • 5 business cases where automation worked
  • 5 business cases where automation didn’t work

Other

Primary Speaker First Name
Stephen
Primary Speaker Last Name
Smith
Primary Speaker Bio
Stephen Smith is a well-respected expert in the fields of data science, predictive analytics and their application in the education, pharmaceutical, healthcare, telecom and finance industries. He co-founded and served as CEO of G7 Research LLC and the Optas Corporation which provided the leading CRM / Marketing Automation solution in the pharmaceutical and healthcare industries. He is a graduate of MIT with research in Artificial Intelligence and did his graduate work at Harvard at one of the first graduate programs in machine learning. He has published to best-selling books with McGraw-Hill: “Data Warehousing, Data Mining and OLAP” and “Building Data Mining Applications for CRM”.
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