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Data Mining: Failure to Launch- Webinar

June 11, 2014 @ 11:00 am

Data Mining: Failure to Launch :How to Get Predictive Modeling Off the Ground and Into Orbit

Weds June 11, 11am US Eastern | 8am US Pacific

Thurs July 31, 4pm US Eastern | 1pm US Pacific

Tues August 19, 11am US Eastern | 8am US Pacific

Attend this free 90-minute vendor-neutral webinar to learn how to get started with predictive analytics and overcome limitations that cause most data mining projects to fall short of their potential. This webinar is intended for stakeholders, functional managers and analytic practitioners in business, industry, government and academia, who have made suMAbstantial investments in data collection, storage, retrieval, visualization and basic analysis but may not have the technical or strategic experience necessary to chart an effective roadmap to uncover the valuable predictive insights hidden within their existing data. No prior knowledge is required.

 

The webinar will cover:

  • How and where to get started
  • Why failure to implement is so common, and why pitfalls are so avoidable
  • Case studies that reveal the rewards of proper design and implementation
  • Why establishing an internal predictive modeling practice is within your reach
  • Tips, tricks and techniques for data preparation and method selection
  • Live participant polls and an interactive guru session with the experts
  • Resources and direction on how to move forward with confidence
  • And more…

Details

Date:
June 11, 2014
Time:
11:00 am
Event Category:
Website:
http://the-modeling-agency.com/data-mining-webinar/

Organizer

The Modeling Agency

Venue

Webinar

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More Information on Predictive Analysis Process

Predictive Analytics Process Flow

For more information of predictive analytics process, please review the overview of each components in the predictive analytics process: data collection (data mining), data analysis, statistical analysis, predictive modeling and predictive model deployment.

Top predictive analytics software and Top predictive analytics open source software.
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