Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Rexer Analytics Survey – are data miners too focused on their models?
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Mining > Rexer Analytics Survey – are data miners too focused on their models?
AnalyticsData MiningDecision Management

Rexer Analytics Survey – are data miners too focused on their models?

JamesTaylor
JamesTaylor
4 Min Read
SHARE

Rexer Analytics have just released the results of their 2011 survey – the 5th annual one, answered by over 1,300 data miners from 60 countries in the first have of 2011. The survey continued to show that CRM/Marketing, Financial and Insurance are the major commercial focus areas for data mining. It also reiterated the top three algorithms – regression, decision trees and cluster analysis while showing a significant increase in text mining with about 1/3 already using it and another 1/3 planning to.

Rexer Analytics have just released the results of their 2011 survey – the 5th annual one, answered by over 1,300 data miners from 60 countries in the first have of 2011. The survey continued to show that CRM/Marketing, Financial and Insurance are the major commercial focus areas for data mining. It also reiterated the top three algorithms – regression, decision trees and cluster analysis while showing a significant increase in text mining with about 1/3 already using it and another 1/3 planning to. Cloud-based platforms are still only 12% with most work done locally on desktops or laptops and open source data mining tools like R are growing rapidly.

A couple of decision management centric observations:

  1. Customer centric goals dominated with 6 of the top 8 goals being directly related to customers. Improving understanding of customers was top (a somewhat passive goal) but retaining them, selling them more and improving their experience all scored highly and these are classic goals also for Decision Management (which is why the Decision Management Summit this year will focus on decisions about customers).
  2. Key drivers for satisfaction with analytic modeling tools were variable discover/profiling, ease of interpretation, model quality metrics and visualization. Sadly ease of model deployment didn’t make the top 10. Analytic modelers are still much more concerned with perfecting their models rather than making sure they can be deployed and used which is a pity as I have noted before.
  3. Model performance was still the top measure of analytic success, beating out financial performance/ROI. Another sign that too many models are concerned only with their model, not on the business performance being improved by their model (the focus of Decision Management).
  4. Reasons for non deployment of models were dominated by effort/cost too high and result not understood but were closely followed by model failures, politics/lack of support and changing business situations (a consequence of taking too long, at least sometimes). Modelers who want to get more of their models deployed and used should perhaps spend more time picking tools that handle deployment well and deploy quickly (see 2) and more time focused on business results to build management support (see 3)!
Taken together these points make me worry that data miners remain too focused on their models and on crafting the perfect model rather than on creating models that can be deployed, are understood and have business support and so will drive business value. I have blogged about industrializing analytics before and posted slides on business friendly data mining, both things I think are needed to address this.

You can find more about the survey on the Rexer Analytics site.

More Read

Mixed-Effects Models in R with Quantum Forest
Formulate a Competitive Growth Strategy with Big Data Analytics
New Big Data Applications
Know Your S#*!: Maximize Web Conversion with A/B Testing
The History of Predictive Analytics [INFOGRAPHIC]

Copyright © 2012 http://jtonedm.com James Taylor

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

sales and data analytics
How Data Analytics Improves Lead Management and Sales Results
Analytics Big Data Exclusive
ai in marketing
How AI and Smart Platforms Improve Email Marketing
Artificial Intelligence Exclusive Marketing
AI Document Verification for Legal Firms: Importance & Top Tools
AI Document Verification for Legal Firms: Importance & Top Tools
Artificial Intelligence Exclusive
AI supply chain
AI Tools Are Strengthening Global Supply Chains
Artificial Intelligence Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

data democratization
CommentaryCulture/LeadershipDecision ManagementInside CompaniesLocationWorkforce Analytics

Rethinking Processes: What an Old Carmaker Can Teach Us About Innovation

12 Min Read

Finally factor of speech clearence (C50) and still more to go.

1 Min Read

Nexidia Advances Customer Interaction Analytics

7 Min Read

Three Implications for the Rise of E-Readers

4 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?